[ { "path": "README.md", "content": "# ML System Design Case Studies Repository\n\n## Description\n\nWelcome to the ML System Design Case Studies Repository! This repository is a comprehensive collection of 300+ case studies from over 80 leading companies, showcasing practical applications and insights into machine learning (ML) system design. Companies like Netflix, Airbnb, and Doordash have shared their experiences, providing a valuable resource for anyone interested in learning how ML is used to improve products and processes.\n\n---\n\n## 🌐 **Featured Resource: HorizonX.live**\n\n> **Supercharge your Research journey with HorizonX.live — the all-in-one platform for all your research needs.**\n\n- 🔍 **Search & Explore**: Instantly find trending ML papers, code, and datasets.\n- 🗂️ **Personalized Libraries**: Save, organize, and annotate your favorite research.\n- 📝 **Interactive Paper Summaries**: Concise, easy-to-digest summaries for each paper.\n## 🚀 Upcoming Features\n\nWe are continuously working to enhance this resource! Here are some exciting features coming soon:\n\n### 🌟 Upcoming Features\n\n- 🟢 **Context-Aware Literature Engine** \n Speed up your literature review with AI that understands your research context.\n\n- **🤖 AI-Powered Brainstorming Engine** \n Collaborate with your intelligent assistant to spark, shape, and elevate breakthrough ideas.\n\n- **🛠️ Low-Code Data Analysis** \n Transform raw data into publication-ready charts and insights—no coding required.\n\n- **👥 Real-Time Collaboration** \n Google Docs meets research-grade Overleaf for seamless teamwork.\n\n- **🔗 Unified Knowledge Nexus** \n A single intelligent workspace that connects your ideas, insights, and research tools.\n\n- **📚 Automated Citation Manager** \n Intelligent reference management system for effortless citations.\n\n- **📝 Smart Formatting Assistant** \n Journal compliance made effortless.\n\n- **🔍 Pre-Publication Quality Check** \n Your 24/7 peer review partner for manuscript quality assurance.\n\n- **💻 On-Demand HPC Access** \n Computing power without the setup headaches.\n\n*Stay tuned for these updates and feel free to suggest features or contribute!*\n\n**Try it now:** https://horizonx.live\n\n---\n\n\n### Features\n\n- **Wide Range of Industries**: Explore case studies from various industries such as tech, finance, healthcare, and more.\n- **Diverse ML Applications**: Learn about different ML use cases, including computer vision (CV), natural language processing (NLP), recommender systems, search and ranking, fraud detection, and many more.\n- **Product Features**: Discover how ML powers specific user-facing features, from grammatical error correction to generating outfit combinations.\n\n### Why This Resource is Valuable\n\n- **Authentic and In-depth**: Each case study is sourced from detailed blogs, papers, or articles about ML systems developed in-house, providing genuine and firsthand insights.\n- **Practical Applications**: The studies cover real-world ML systems that are actively used in production, offering practical and proven examples.\n- **Focused and Detailed**: The case studies focus on specific ML use cases, providing clear and comprehensive information on the target users, model designs, evaluation criteria, and deployment architectures.\n\n### How to Use\n\n- **Short Description**: Use the discription to quickly find case studies relevant to your interests.\n- **Explore and Learn**: Dive into the detailed descriptions and implementations to gain a deeper understanding of ML system design.\n- **Share and Collaborate**: If you find the database helpful, spread the word and contribute to the repository by suggesting new case studies.\n\n## Enjoy exploring the wealth of knowledge in these case studies and enhance your understanding of machine learning system design!\n\n# Real-world ML systems\n| Index | Company | Industry | Description (< 5 words) | Title | Year |\n|--------:|:---------------------|:------------------------------------------|:--------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------:|\n| 1 | Stripe | Fintech and banking | Prevent fraudelent transactions | [How we built it: Stripe Radar](https://stripe.com/blog/how-we-built-it-stripe-radar) | 2023 |\n| 2 | Walmart | E-commerce and retail | Recommend complementary items | [Personalized ‘Complete the Look’ model](https://medium.com/walmartglobaltech/personalized-complete-the-look-model-ea093aba0b73) | 2023 |\n| 3 | Uber | Delivery and mobility | Forecast demand for airport rides | [Demand and ETR Forecasting at Airports](https://www.uber.com/en-GB/blog/demand-and-etr-forecasting-at-airports/) | 2023 |\n| 4 | Pinterest | Social platforms | Prevent advertiser churn | [An ML based approach to proactive advertiser churn prevention](https://medium.com/pinterest-engineering/an-ml-based-approach-to-proactive-advertiser-churn-prevention-3a7c0c335016) | 2023 |\n| 5 | Stitch Fix | E-commerce and retail | Generate ad headlines | [A New Era of Creativity: Expert-in-the-loop Generative AI at Stitch Fix](https://multithreaded.stitchfix.com/blog/2023/03/06/expert-in-the-loop-generative-ai-at-stitch-fix/) | 2023 |\n| 6 | Swiggy | Delivery and mobility | Recommend items to order | [Building a mind reader at Swiggy using Data Science](https://bytes.swiggy.com/building-a-mind-reader-at-swiggy-using-data-science-5a5c38aa6c17) | 2023 |\n| 7 | Microsoft | Tech | Diagnose production incidents with LLM | [Large-language models for automatic cloud incident management](https://www.microsoft.com/en-us/research/blog/large-language-models-for-automatic-cloud-incident-management/) | 2023 |\n| 8 | Foodpanda | Delivery and mobility | Optimize menu sorting order | [Menu Ranking](https://medium.com/foodpanda-data/menu-ranking-422ad21f381e) | 2023 |\n| 9 | Zillow | E-commerce and retail | Estimate the house market value | [Building the Neural Zestimate](https://www.zillow.com/tech/building-the-neural-zestimate/) | 2023 |\n| 10 | Airbnb | Travel,E-commerce and retail | Identify user interests | [Prioritizing Home Attributes Based on Guest Interest](https://medium.com/airbnb-engineering/prioritizing-home-attributes-based-on-guest-interest-3c49b827e51a) | 2023 |\n| 11 | GitHub | Tech | Generate code and code suggestions | [Inside GitHub: Working with the LLMs behind GitHub Copilot](https://github.blog/2023-05-17-inside-github-working-with-the-llms-behind-github-copilot/) | 2023 |\n| 12 | DoorDash | Delivery and mobility | Optimize courier waiting time | [Lifecycle of a Successful ML Product: Reducing Dasher Wait Times](https://doordash.engineering/2023/02/15/lifecycle-of-a-successful-ml-product-reducing-dasher-wait-times/) | 2023 |\n| 13 | Linkedin | Social platforms | Select best payment gateway | [Improving the customer’s experience via ML-driven payment routing](https://engineering.linkedin.com/blog/2023/improving-the-customer-s-experience-via-ml-driven-payment-routin) | 2023 |\n| 14 | Wayfair | E-commerce and retail | Predict delivery times | [Delivery-Date Prediction](https://www.aboutwayfair.com/careers/tech-blog/delivery-date-prediction) | 2023 |\n| 15 | Linkedin | Social platforms | Detect viral spam | [Viral spam content detection at LinkedIn](https://engineering.linkedin.com/blog/2023/viral-spam-content-detection-at-linkedin) | 2023 |\n| 16 | Lyft | Delivery and mobility | Recommend content in app | [The Recommendation System at Lyft](https://eng.lyft.com/the-recommendation-system-at-lyft-67bc9dcc1793) | 2023 |\n| 17 | Honeycomb | Tech | Generate queries with natural language | [All the Hard Stuff Nobody Talks About when Building Products with LLMs](https://www.honeycomb.io/blog/hard-stuff-nobody-talks-about-llm) | 2023 |\n| 18 | Zalando | E-commerce and retail | Forecast demand in fashion e-commerce | [Deep Learning based Forecasting: a case study from the online fashion industry](https://arxiv.org/abs/2305.14406) | 2023 |\n| 19 | Etsy | E-commerce and retail | Recommend relevant marketplace items | [How We Built a Multi-Task Canonical Ranker for Recommendations at Etsy](https://www.etsy.com/uk/codeascraft/how-we-built-a-multi-task-canonical-ranker-for-recommendations-at-etsy) | 2023 |\n| 20 | Yelp | Social platforms | Organize e-commerce content using embeddings | [Yelp Content As Embeddings](https://engineeringblog.yelp.com/2023/04/yelp-content-as-embeddings.html) | 2023 |\n| 21 | Monzo | Fintech and banking | Select relevant marketing messages | [Optimising marketing messages for Monzo users](https://medium.com/data-monzo/optimising-marketing-messages-for-monzo-users-3fe805f24572) | 2023 |\n| 22 | Monzo | Fintech and banking | Detect patterns in text data | [Using topic modelling to understand customer saving goals](https://medium.com/data-monzo/using-topic-modelling-to-understand-customer-saving-goals-2bb06f00ce2d) | 2023 |\n| 23 | Wayfair | E-commerce and retail | Predict new product’s sales potential | [How Wayfair uses “Predicted Winners” Models to Accelerate Success for New Products](https://www.aboutwayfair.com/careers/tech-blog/how-wayfair-uses-predicted-winners-models-to-accelerate-success-for-new-products) | 2023 |\n| 24 | Airbnb | Travel,E-commerce and retail | Personalized listing search | [Learning To Rank Diversely](https://medium.com/airbnb-engineering/learning-to-rank-diversely-add6b1929621) | 2023 |\n| 25 | Twitter | Social platforms | Recommend interesting tweets | [Twitter's Recommendation Algorithm](https://blog.twitter.com/engineering/en_us/topics/open-source/2023/twitter-recommendation-algorithm ) | 2023 |\n| 26 | DoorDash | Delivery and mobility | Predict if a store is open | [How DoorDash Upgraded a Heuristic with ML to Save Thousands of Canceled Orders](https://doordash.engineering/2023/01/10/how-doordash-upgraded-a-heuristic-with-ml-to-save-thousands-of-canceled-orders/) | 2023 |\n| 27 | Wayfair | E-commerce and retail | Identify business customers | [Hamlet: Wayfair's ML Approach to Identifying Business Shopper](https://www.aboutwayfair.com/careers/tech-blog/hamlet) | 2023 |\n| 28 | Wayfair | E-commerce and retail | Detect fraud with embeddings | [Introducing Melange: A Customer Journey Embedding System for Improving Fraud and Policy Abuse Detection](https://www.aboutwayfair.com/careers/tech-blog/introducing-melange-a-customer-journey-embedding-system-for-improving-fraud-and-scam-detection) | 2023 |\n| 29 | Airbnb | Travel,E-commerce and retail | Improve travel search experience | [Building Airbnb Categories with ML & Human in the Loop](https://medium.com/airbnb-engineering/building-airbnb-categories-with-ml-human-in-the-loop-35b78a837725) | 2023 |\n| 30 | Spotify | Media and streaming | Automatically generate ad content | [How We Automated Content Marketing to Acquire Users at Scale](https://engineering.atspotify.com/2023/11/how-we-automated-content-marketing-to-acquire-users-at-scale/) | 2023 |\n| 31 | Instacart | E-commerce and retail | Predict availability of food items | [How Instacart Modernized the Prediction of Real Time Availability for Hundreds of Millions of Items While Saving Costs](https://tech.instacart.com/how-instacart-modernized-the-prediction-of-real-time-availability-for-hundreds-of-millions-of-items-59b2a82c89fe) | 2023 |\n| 32 | Linkedin | Social platforms | Personalize the homepage feed | [Enhancing homepage feed relevance by harnessing the power of large corpus sparse ID embeddings](https://engineering.linkedin.com/blog/2023/enhancing-homepage-feed-relevance-by-harnessing-the-power-of-lar) | 2023 |\n| 33 | Doordash | Delivery and mobility | Forecast order volumes and deliveries | [How DoorDash Built an Ensemble Learning Model for Time Series Forecasting](https://doordash.engineering/2023/06/20/how-doordash-built-an-ensemble-learning-model-for-time-series-forecasting/) | 2023 |\n| 34 | Expedia | Travel,E-commerce and retail | Forecast flight prices | [Using Synthetic Search Data for Flights Price Forecasting](https://medium.com/expedia-group-tech/using-synthetic-search-data-for-flights-price-forecasting-4cf3277afdaf) | 2023 |\n| 35 | Nextdoor | Social platforms | Generate engaging email subject lines | [Let AI Entertain You: Increasing User Engagement with Generative AI and Rejection Sampling](https://engblog.nextdoor.com/let-ai-entertain-you-increasing-user-engagement-with-generative-ai-and-rejection-sampling-50a402264f56) | 2023 |\n| 36 | Criteo | Tech | Figure out users' preferences | [Recommender systems need a user model](https://medium.com/criteo-engineering/recommender-systems-need-a-user-model-c3b3790311bf) | 2023 |\n| 37 | Apple | Tech | Identify objects on images | [Fast Class-Agnostic Salient Object Segmentation](https://machinelearning.apple.com/research/salient-object-segmentation) | 2023 |\n| 38 | Zillow | E-commerce and retail | Identify and block unwanted callers | [SpectroBrain: Detecting Phone Spam with Semi-Supervised Learning](https://www.zillow.com/tech/spectrobrain-detecting-phone-spam-with-semi-supervised-learning/) | 2023 |\n| 39 | Algolia | Tech | Suggest relevant search queries | [Feature Spotlight: Query Suggestions](https://www.algolia.com/blog/product/feature-spotlight-query-suggestions/) | 2023 |\n| 40 | Netflix | Media and streaming | In-video search | [Building In-Video Search](https://netflixtechblog.com/building-in-video-search-936766f0017c) | 2023 |\n| 41 | Grab | Delivery and mobility,Banking and finance | Automatically tag sensitive data | [LLM-powered data classification for data entities at scale](https://engineering.grab.com/llm-powered-data-classification) | 2023 |\n| 42 | Doordash | Delivery and mobility | Accurately forecast demand during holidays | [How DoorDash Improves Holiday Predictions via Cascade ML Approach](https://doordash.engineering/2023/08/31/how-doordash-improves-holiday-predictions-via-cascade-ml-approach/) | 2023 |\n| 43 | Netflix | Media and streaming | Personalize video clips | [The Next Step in Personalization: Dynamic Sizzles](https://netflixtechblog.com/the-next-step-in-personalization-dynamic-sizzles-4dc4ce2011ef) | 2023 |\n| 44 | BlaBlaCar | Delivery and mobility | Prevent phishing and payment fraud | [How we used machine learning to fight fraud at BlaBlaCar — Part 1](https://medium.com/blablacar/how-we-used-machine-learning-to-fight-fraud-at-blablacar-part-1-3b976c9dcdf6) | 2023 |\n| 45 | Instacart | E-commerce and retail | Personalize user experience by recommending relevant products | [Using Contextual Bandit models in large action spaces at Instacart](https://tech.instacart.com/using-contextual-bandit-models-in-large-action-spaces-at-instacart-cb7ab4d8fa4f) | 2023 |\n| 46 | Pinterest | Social platforms | Recommend similar visual content | [Training Foundation Improvements for Closeup Recommendation Ranker](https://medium.com/pinterest-engineering/training-foundation-improvements-for-closeup-recommendation-ranker-67d90603426e) | 2023 |\n| 47 | Spotify | Media and streaming | Recommend new complementary music | [Spotify Track Neural Recommender System](https://medium.com/stanford-cs224w/spotify-track-neural-recommender-system-51d266e31e16) | 2023 |\n| 48 | Meta | Social platforms | Generate code with LLM | [Introducing Code Llama, a state-of-the-art large language model for coding](https://ai.meta.com/blog/code-llama-large-language-model-coding/) | 2023 |\n| 49 | Grammarly | Tech | Suggest gender-inclusive grammatical error corrections | [Improving the Performance of NLP Systems on the Gender-Neutral “They”](https://arxiv.org/abs/2306.07415) | 2023 |\n| 50 | Netflix | Media and streaming | Detect speech and music in audio | [Detecting Speech and Music in Audio Content](https://netflixtechblog.com/detecting-speech-and-music-in-audio-content-afd64e6a5bf8) | 2023 |\n| 51 | Salesforce | Tech | Extract relevant information from a knowledge article | [Resolve Cases Quickly with Interactive Einstein Search Answers](https://blog.salesforceairesearch.com/einstein-search-answers/) | 2023 |\n| 52 | Etsy | E-commerce and retail | Show relevant ads | [Leveraging Real-Time User Actions to Personalize Etsy Ads](https://arxiv.org/pdf/2302.01255.pdf) | 2023 |\n| 53 | GitHub | Tech | AI copilot for code generation | [How to build an enterprise LLM application: Lessons from GitHub Copilot](https://github.blog/2023-09-06-how-to-build-an-enterprise-llm-application-lessons-from-github-copilot/) | 2023 |\n| 54 | Uber | Delivery and mobility | Detect potential fraudulent entities | [Risk Entity Watch – Using Anomaly Detection to Fight Fraud](https://www.uber.com/en-IN/blog/risk-entity-watch/?uclick_id=9c4355d3-795f-4b1d-b18e-4b8b4c8ed29f) | 2023 |\n| 55 | Expedia | Travel,E-commerce and retail | Predict Customer Lifetime Value (CLV) | [Expedia Group’s Customer Lifetime Value Prediction Model](https://medium.com/expedia-group-tech/expedia-groups-customer-lifetime-value-prediction-model-7927cdd44342) | 2023 |\n| 56 | Dailymotion | Media and streaming | Recommend diversified video content | [Reinvent your recommender system using Vector Database and Opinion Mining](https://medium.com/dailymotion/reinvent-your-recommender-system-using-vector-database-and-opinion-mining-a4fadf97d020) | 2023 |\n| 57 | Swiggy | Delivery and mobility | Predict food delivery time | [Where is my order? — Part I](https://bytes.swiggy.com/how-ml-powers-when-is-my-order-coming-part-i-4ef24eae70da) | 2023 |\n| 58 | Swiggy | Delivery and mobility | Сonversational and open-ended search | [Swiggy’s Generative AI Journey: A Peek Into the Future](https://bytes.swiggy.com/swiggys-generative-ai-journey-a-peek-into-the-future-2193c7166d9a) | 2023 |\n| 59 | New York Times | Media and streaming | Recommend recipes to readers | [How The New York Times Cooking Team Makes Personalized Recipe Recommendations](https://open.nytimes.com/how-the-new-york-times-cooking-team-makes-personalized-recipe-recommendations-7b86df9b22ec) | 2023 |\n| 60 | Expedia | Travel,E-commerce and retail | Suggest diverse travel recommendations | [Generating Diverse Travel Recommendations](https://medium.com/expedia-group-tech/generating-diverse-travel-recommendations-76688f49c812) | 2023 |\n| 61 | Stitch Fix | E-commerce and retail | Personalize styling recommendations | [Accelerating AI: Implementing Multi-GPU Distributed Training for Personalized Recommendations](https://multithreaded.stitchfix.com/blog/2023/06/08/distributed-model-training/) | 2023 |\n| 62 | Doordash | Delivery and mobility | Areas for using Generative AI | [DoorDash identifies Five big areas for using Generative AI](https://doordash.engineering/2023/04/26/doordash-identifies-five-big-areas-for-using-generative-ai/) | 2023 |\n| 63 | Etsy | E-commerce and retail | Search by image | [From Image Classification to Multitask Modeling: Building Etsy’s Search by Image Feature](https://www.etsy.com/codeascraft/from-image-classification-to-multitask-modeling-building-etsys-search-by-image-feature) | 2023 |\n| 64 | Spotify | Media and streaming | Generate audio podcast previews | [Large-Scale Generation of ML Podcast Previews at Spotify with Google Dataflow](https://engineering.atspotify.com/2023/04/large-scale-generation-of-ml-podcast-previews-at-spotify-with-google-dataflow/) | 2023 |\n| 65 | Delivery Hero | Delivery and mobility | Better understand user behavior | [Personalisation @ Delivery Hero: Understanding Customers](https://tech.deliveryhero.com/personalisation-at-delivery-hero-understanding-customers/) | 2023 |\n| 66 | Swiggy | Delivery and mobility | Predict food delivery time | [Predicting Food Delivery Time at Cart](https://bytes.swiggy.com/predicting-food-delivery-time-at-cart-cda23a84ba63) | 2023 |\n| 67 | Netflix | Media and streaming | Generate content recommendations for users | [Lessons Learnt From Consolidating ML Models in a Large Scale Recommendation System](https://netflixtechblog.medium.com/lessons-learnt-from-consolidating-ml-models-in-a-large-scale-recommendation-system-870c5ea5eb4a ) | 2023 |\n| 68 | Linkedin | Social platforms | Show relevant jobs in search | [How LinkedIn Is Using Embeddings to Up Its Match Game for Job Seekers](https://engineering.linkedin.com/blog/2023/how-linkedin-is-using-embeddings-to-up-its-match-game-for-job-se) | 2023 |\n| 69 | Expedia | Travel,E-commerce and retail | Alert users about optimal deals | [Increasing Travelers’ Engagement Through Price Alerts](https://medium.com/expedia-group-tech/increasing-travelers-engagement-through-relevant-price-alerts-at-expedia-group-75aa6a377864) | 2023 |\n| 70 | Walmart | E-commerce and retail | Resolve entities and detect relationships | [Exploring an Entity Resolution Framework Across Various Use Cases](https://medium.com/walmartglobaltech/exploring-an-entity-resolution-framework-across-various-use-cases-cb172632e4ae) | 2023 |\n| 71 | Thoughtworks | Tech | AI copilot for product strategy | [Building Boba AI](https://martinfowler.com/articles/building-boba.html) | 2023 |\n| 72 | Grab | Delivery and mobility,Banking and finance | Automatically detect new fraud types | [Unsupervised graph anomaly detection - Catching new fraudulent behaviours](https://engineering.grab.com/graph-anomaly-model) | 2023 |\n| 73 | Dropbox | Tech | Identify date formats in file names | [Is this a date? Using ML to identify date formats in file names](https://dropbox.tech/machine-learning/using-ml-to-identify-date-formats-in-file-names) | 2023 |\n| 74 | Grab | Delivery and mobility,Banking and finance | Сreate scalable lookalike audiences | [Stepping up marketing for advertisers: Scalable lookalike audience](https://engineering.grab.com/scalable-lookalike-audiences) | 2023 |\n| 75 | Wayfair | E-commerce and retail | Send relevant communications to customers | [Griffin: How Wayfair Leverages Reinforcement Learning to Send Customers Relevant Communications](https://www.aboutwayfair.com/careers/tech-blog/griffin-how-wayfair-leverages-reinforcement-learning-to-send-customers-relevant-communications) | 2023 |\n| 76 | Whatnot | E-commerce and retail | Detect marketplace spam | [How Whatnot Utilizes Generative AI to Enhance Trust and Safety](https://medium.com/whatnot-engineering/how-whatnot-utilizes-generative-ai-to-enhance-trust-and-safety-c7968eb6315e) | 2023 |\n| 77 | Instacart | E-commerce and retail | Predict grocery item availability | [How Instacart’s Item Availability Evolved Over the Pandemic](https://www.instacart.com/company/how-its-made/how-instacarts-item-availability-evolved-over-the-pandemic/) | 2023 |\n| 78 | Instacart | E-commerce and retail | Predict availability of food items | [Instacart’s Item Availability Architecture: Solving for scale and consistency](https://tech.instacart.com/instacarts-item-availability-architecture-solving-for-scale-and-consistency-f5661acb20a6) | 2023 |\n| 79 | BlaBlaCar | Delivery and mobility | Prevent phishing and payment fraud | [How we built our machine learning pipeline to fight fraud at BlaBlaCar — Part 2](https://medium.com/blablacar/how-we-built-our-machine-learning-pipeline-to-fight-fraud-at-blablacar-part-2-476335f459b4) | 2023 |\n| 80 | Salesforce | Tech | Summarize Slack conversations | [AI Summarist: Get Your Time Back on Slack, Boost Productivity & Focus, Personalize Information Consumption](https://blog.salesforceairesearch.com/ai-summarist-slack-productivity) | 2023 |\n| 81 | Meta | Social platforms | Show users relevant content at scale | [Scaling the Instagram Explore recommendations system](https://engineering.fb.com/2023/08/09/ml-applications/scaling-instagram-explore-recommendations-system/) | 2023 |\n| 82 | Delivery Hero | Delivery and mobility | Recommend restaurants for new customers | [Personalisation @ Delivery Hero: Ranking restaurants for new users](https://tech.deliveryhero.com/personalisation-delivery-hero-ranking-restaurants-for-new-users/) | 2023 |\n| 83 | Swiggy | Delivery and mobility | Predict food delivery time | [How ML Powers — When is my order coming? — Part II](https://bytes.swiggy.com/how-ml-powers-when-is-my-order-coming-part-ii-eae83575e3a9) | 2023 |\n| 84 | Salesforce | Tech | Recommend apps in the marketplace | [On the Diversity and Explainability of Enterprise App Recommendation Systems](https://blog.salesforceairesearch.com/diversity-explainability-enterprise-app-recommendation-systems/) | 2023 |\n| 85 | Grab | Delivery and mobility,Banking and finance | Optimize promotional campaigns | [Scaling marketing for merchants with targeted and intelligent promos](https://engineering.grab.com/scaling-marketing-for-merchants) | 2023 |\n| 86 | GitHub | Tech | Automated code reviews and PR tagging | [Generative AI-enabled compliance for software development](https://github.blog/2023-04-11-generative-ai-enabled-compliance-for-software-development) | 2023 |\n| 87 | Delivery Hero | Delivery and mobility | Recommend restaurants | [Don’t Worry, We Got You: Personalised Model](https://tech.deliveryhero.com/dont-worry-we-got-you-personalised-model-2/) | 2023 |\n| 88 | OLX | E-commerce and retail | Predict order delivery time | [Machine Learning for Delivery Time Estimation](https://tech.olx.com/machine-learning-for-delivery-time-estimation-1-591c8df849a0) | 2023 |\n| 89 | Spotify | Media and streaming | Target in-app messaging | [Experimenting with Machine Learning to Target In-App Messaging](https://engineering.atspotify.com/2023/06/experimenting-with-machine-learning-to-target-in-app-messaging/) | 2023 |\n| 90 | Nubank | Fintech and banking | Automatically route customer phone calls | [Presenting Precog, Nubank’s Real Time Event AI](https://building.nubank.com.br/presenting-precog-nubanks-real-time-event-ai/) | 2023 |\n| 91 | Instacart | E-commerce and retail | Build an internal AI assistant | [Scaling Productivity with Ava — Instacart’s Internal AI Assistant](https://tech.instacart.com/scaling-productivity-with-ava-instacarts-internal-ai-assistant-ed7f02558d84) | 2023 |\n| 92 | Meta | Social platforms | Translate and transcribe across speech and text | [Bringing the world closer together with a foundational multimodal model for speech translation](https://ai.meta.com/blog/seamless-m4t/) | 2023 |\n| 93 | Vimeo | Media and streaming | Customer support AI assistant | [From idea to reality: Elevating our customer support through generative AI](https://medium.com/vimeo-engineering-blog/from-idea-to-reality-elevating-our-customer-support-through-generative-ai-101a2c5ea680) | 2023 |\n| 94 | Ebay | E-commerce and retail | Recommend relevant e-commerce items | [Building a Deep Learning Based Retrieval System for Personalized Recommendations](https://tech.ebayinc.com/engineering/building-a-deep-learning-based-retrieval-system-for-personalized-recommendations/) | 2022 |\n| 95 | Mercado Libre | Delivery and mobility | Predict product dimensions for delivery | [Predicting package dimensions based on a similarity model at Mercado Libre](https://medium.com/mercadolibre-tech/predicting-package-dimensions-based-on-a-similarity-model-at-mercado-libre-d64a9dd4351d) | 2022 |\n| 96 | Doordash | Delivery and mobility | Recommend substitute items | [Evolving DoorDash’s Substitution Recommendations Algorithm](https://doordash.engineering/2022/09/08/evolving-doordashs-substitution-recommendations-algorithm/) | 2022 |\n| 97 | Pinterest | Social platforms | Personalize homepage contents | [How Pinterest Leverages Realtime User Actions in Recommendation to Boost Homefeed Engagement Volume](https://medium.com/pinterest-engineering/how-pinterest-leverages-realtime-user-actions-in-recommendation-to-boost-homefeed-engagement-volume-165ae2e8cde8 ) | 2022 |\n| 98 | Instacart | Delivery and mobility | Search food and grocery items | [How Instacart Uses Embeddings to Improve Search Relevance](https://tech.instacart.com/how-instacart-uses-embeddings-to-improve-search-relevance-e569839c3c36) | 2022 |\n| 99 | Walmart | E-commerce and retail | Assist in e-commerce shopping | [A Unified Multi-task Model for Supporting Multiple Virtual Assistants in Walmart](https://medium.com/walmartglobaltech/a-unified-multi-task-model-for-supporting-multiple-virtual-assistants-in-walmart-2b077c2c96e) | 2022 |\n| 100 | Spotify | Media and streaming | Search for podcasts | [Introducing Natural Language Search for Podcast Episodes](https://engineering.atspotify.com/2022/03/introducing-natural-language-search-for-podcast-episodes/) | 2022 |\n| 101 | Nextdoor | Social platforms | Predict harmful comments | [Using predictive technology to foster constructive conversations](https://engblog.nextdoor.com/using-predictive-technology-to-foster-constructive-conversations-4af437942bd4) | 2022 |\n| 102 | Walmart | E-commerce and retail | Fill shopping cart via voice dialog | [Voice Reorder Experience: add Multiple Product Items to your shopping cart](https://medium.com/walmartglobaltech/voice-reorder-experience-add-multiple-product-items-to-your-shopping-cart-59d20fc61797) | 2022 |\n| 103 | Expedia | Travel,E-commerce and retail | Categorize customer feedback | [Categorising Customer Feedback Using Unsupervised Learning](https://medium.com/expedia-group-tech/categorising-customer-feedback-using-unsupervised-learning-8608c1e62d48) | 2022 |\n| 104 | Foodpanda | Delivery and mobility | Classify restaurants and cuisines | [Classifying restaurant cuisines with subjective labels](https://medium.com/foodpanda-data/classifying-restaurant-cuisines-with-subjective-labels-fa10012d18a9 ) | 2022 |\n| 105 | Ebay | Social platforms | Recommend products and content | [Multi-Relevance Ranking Model for Similar Item Recommendation](https://tech.ebayinc.com/engineering/multi-relevance-ranking-model-for-similar-item-recommendation/) | 2022 |\n| 106 | Gousto | Delivery and mobility | Predict subscription churn | [Using Data Science to Retain Customers](https://medium.com/gousto-engineering-techbrunch/using-data-science-to-retain-customers-63f19a03a0b6) | 2022 |\n| 107 | Google | Tech | Generate summaries | [Auto-generated Summaries in Google Docs](https://ai.googleblog.com/2022/03/auto-generated-summaries-in-google-docs.html) | 2022 |\n| 108 | Yelp | Social platforms | Personalize recommendations | [Beyond Matrix Factorization: Using hybrid features for user-business recommendations](https://engineeringblog.yelp.com/2022/04/beyond-matrix-factorization-using-hybrid-features-for-user-business-recommendations.html) | 2022 |\n| 109 | PayPal | Fintech and banking | Prioritize sales leads | [Sales Pipeline Management with Machine Learning: A Lightweight Two-Layer Ensemble Classifier Framework](https://medium.com/paypal-tech/sales-pipeline-management-with-machine-learning-15398bab913b) | 2022 |\n| 110 | Grubhub | Delivery and mobility | Forecast order volume | [Forecasting Grubhub Order Volume At Scale](https://bytes.grubhub.com/forecasting-grubhub-order-volume-at-scale-a966c2f901d2) | 2022 |\n| 111 | Github | Tech | Detect vulnerabilities in code | [Leveraging machine learning to find security vulnerabilities](https://github.blog/2022-02-17-leveraging-machine-learning-find-security-vulnerabilities/) | 2022 |\n| 112 | Uber | Delivery and mobility | Detect payment fraud | [Project RADAR: Intelligent Early Fraud Detection System with Humans in the Loop](https://www.uber.com/en-GB/blog/project-radar-intelligent-early-fraud-detection/) | 2022 |\n| 113 | Gojek | Delivery and mobility | Predict food delivery times | [How We Estimate Food Debarkation Time With 'Tensoba'](https://www.gojek.io/blog/food-debarkation-tensoba) | 2022 |\n| 114 | Uber | Delivery and mobility | Predict estimated time of arrival | [DeepETA: How Uber Predicts Arrival Times Using Deep Learning](https://www.uber.com/en-GB/blog/deepeta-how-uber-predicts-arrival-times/) | 2022 |\n| 115 | Trivago | Travel,E-commerce and retail | Optimize accommodation ranking | [Explore-exploit dilemma in Ranking model](https://tech.trivago.com/post/2022-11-04-explore-exploit-dilemma-in-ranking-model) | 2022 |\n| 116 | Gousto | Delivery and mobility | Recommend food items and recipes | [Gousto R-series Vol 2: Tackling the Cold-Start Problem in Recipe Recommendation Engine](https://medium.com/gousto-engineering-techbrunch/gousto-r-series-vol-2-tackling-the-cold-start-problem-in-recipe-recommendation-engine-af92a434805f) | 2022 |\n| 117 | Spotify | Media and streaming | Forecast user activity metrics | [How We Built Infrastructure to Run User Forecasts at Spotify](https://engineering.atspotify.com/2022/06/how-we-built-infrastructure-to-run-user-forecasts-at-spotify/ ) | 2022 |\n| 118 | Google | Tech | Summarize conversations | [Conversation Summaries in Google Chat](https://ai.googleblog.com/2022/11/conversation-summaries-in-google-chathtml) | 2022 | | |\n| 119 | Airbnb | Travel,E-commerce and retail | Improve travel search experience | [Building Airbnb Categories with ML and Human-in-the-Loop](https://medium.com/airbnb-engineering/building-airbnb-categories-with-ml-and-human-in-the-loop-e97988e70ebb) | 2022 |\n| 120 | Uber | Delivery and mobility | Send timely push notifications | [How Uber Optimizes the Timing of Push Notifications using ML and Linear Programming](https://www.uber.com/en-US/blog/how-uber-optimizes-push-notifications-using-ml/) | 2022 |\n| 121 | Meta | Social platforms | Personalize daily digest notifications | [Improving Instagram notification management with machine learning and causal inference](https://engineering.fb.com/2022/10/31/ml-applications/instagram-notification-management-machine-learning/) | 2022 |\n| 122 | Instacart | Delivery and mobility | Recommend relevant food items | [Personalizing Recommendations for a Learning User](https://www.instacart.com/company/how-its-made/personalizing-recommendations-for-a-learning-user/) | 2022 |\n| 123 | Expedia | Travel,E-commerce and retail | Rank relevant travel deals | [How to Optimise Rankings with Cascade Bandits](https://medium.com/expedia-group-tech/how-to-optimise-rankings-with-cascade-bandits-5d92dfa0f16b) | 2022 |\n| 124 | Doordash | Delivery and mobility | Personalize recommendations on homepage | [Homepage Recommendation with Exploitation and Exploration](https://doordash.engineering/2022/10/05/homepage-recommendation-with-exploitation-and-exploration/) | 2022 |\n| 125 | Linkedin | Social platforms | Improve post search functionality | [Improving Post Search at LinkedIn](https://engineering.linkedin.com/blog/2022/improving-post-search-at-linkedin) | 2022 |\n| 126 | Artefact | Tech | Evaluate success of past promotions | [Forecasting something that never happened: how we estimated past promotions profitability](https://medium.com/artefact-engineering-and-data-science/forecasting-something-that-never-happened-how-we-estimated-past-promotions-profitability-5f55cfa1d477) | 2022 |\n| 127 | Doordash | Delivery and mobility | Find high-value merchants | [Building the Model Behind DoorDash’s Expansive Merchant Selection](https://doordash.engineering/2022/04/19/building-merchant-selection/) | 2022 |\n| 128 | Grammarly | Tech | Suggest text edits | [Under the Hood of the Grammarly Editor, Part Two: How Suggestions Work](https://www.grammarly.com/blog/engineering/how-suggestions-work-grammarly-editor/) | 2022 |\n| 129 | Amazon | Media and streaming | Suggest music to listen to | [The Amazon Music conversational recommender is hitting the right notes](https://www.amazon.science/latest-news/how-amazon-music-uses-recommendation-system-machine-learning) | 2022 |\n| 130 | Snap | Social platforms | Rank relevant ads | [Machine Learning for Snapchat Ad Ranking](https://eng.snap.com/machine-learning-snap-ad-ranking) | 2022 |\n| 131 | Instacart | E-commerce and retail | Autocomplete user searches in e-commerce | [How Instacart Uses Machine Learning-Driven Autocomplete to Help People Fill Their Carts](https://tech.instacart.com/how-instacart-uses-machine-learning-driven-autocomplete-to-help-people-fill-their-carts-9bc56d22bafb) | 2022 |\n| 132 | Zillow | E-commerce and retail | Select tags for product listings | [Helping Home Shoppers Find a Home to Love Through Home Insights](https://www.zillow.com/tech/helping-shoppers-find-a-home-using-home-insights/) | 2022 |\n| 133 | Netflix | Media and streaming | Detect account or content fraud | [Machine Learning for Fraud Detection in Streaming Services](https://netflixtechblog.medium.com/machine-learning-for-fraud-detection-in-streaming-services-b0b4ef3be3f6) | 2022 |\n| 134 | Airbnb | Travel,E-commerce and retail | Improve customer support | [How AI Text Generation Models Are Reshaping Customer Support at Airbnb](https://medium.com/airbnb-engineering/how-ai-text-generation-models-are-reshaping-customer-support-at-airbnb-a851db0b4fa3) | 2022 |\n| 135 | Linkedin | Social platforms | Predict churn and upsell products | [The journey to build an explainable AI-driven recommendation system](https://engineering.linkedin.com/blog/2022/the-journey-to-build-an-explainable-ai-driven-recommendation-sys) | 2022 |\n| 136 | Autotrader | E-commerce and retail | Personalize automotive search results | [Real-Time Personalisation of Search Results with Auto Trader's Customer Data Platform](https://engineering.autotrader.co.uk/2022/11/23/real-time-personalisation-of-search-results-with-auto-traders-customer-data-platform.html) | 2022 |\n| 137 | Peloton | Tech | Recommend fitness training videos | [How We Built: An Early-Stage Machine Learning Model for Recommendations](https://www.onepeloton.com/press/articles/how-we-built-machine-learning) | 2022 |\n| 138 | Walmart | E-commerce and retail | Categorize e-commerce products | [Semantic Label Representation with an Application on Multimodal Product Categorization](https://medium.com/walmartglobaltech/semantic-label-representation-with-an-application-on-multimodal-product-categorization-63d668b943b7) | 2022 |\n| 139 | Doordash | Delivery and mobility | Search food and grocery items | [3 Changes to Expand DoorDash’s Product Search Beyond Delivery](https://doordash.engineering/2022/05/10/3-changes-to-expand-doordashs-product-search/) | 2022 |\n| 140 | Faire | E-commerce and retail | Rank e-commerce items (feature store) | [Real-time ranking at Faire part 2: the feature store](https://craft.faire.com/real-time-ranking-at-faire-part-2-the-feature-store-3f1013d3fe5d) | 2022 |\n| 141 | New York Times | Media and streaming | Personalize paywall limits | [How The New York Times Uses Machine Learning To Make Its Paywall Smarter](https://open.nytimes.com/how-the-new-york-times-uses-machine-learning-to-make-its-paywall-smarter-e5771d5f46f8) | 2022 |\n| 142 | Linkedin | Social platforms | Predict ad click-through rate | [Challenges and practical lessons from building a deep-learning-based ads CTR prediction model](https://engineering.linkedin.com/blog/2022/challenges-and-practical-lessons-from-building-a-deep-learning-b) | 2022 |\n| 143 | Zillow | E-commerce and retail | Identify customers that are likely to convert | [Identifying High-Intent Buyers](https://www.zillow.com/tech/identifying-high-intent-buyers/) | 2022 | | |\n| 144 | Netflix | Media and streaming | Recommend content to view | [Reinforcement Learning for Budget Constrained Recommendations](https://netflixtechblog.com/reinforcement-learning-for-budget-constrained-recommendations-6cbc5263a32a) | 2022 |\n| 145 | Walmart | E-commerce and retail | Forecast anomalies in refrigeration | [Forecast Anomalies in Refrigeration with PySpark & Sensor-data](https://medium.com/walmartglobaltech/forecast-anomalies-in-refrigeration-with-pyspark-sensor-data-195f23ae24e2) | 2022 |\n| 146 | Stitch Fix | E-commerce and retail | Recommend e-commerce items | [Client Time Series Model: a Multi-Target Recommender System based on Temporally-Masked Encoders](https://multithreaded.stitchfix.com/blog/2022/10/14/client-time-series-model/) | 2022 |\n| 147 | Gojek | Delivery and mobility | Predict estimated time of delivery | [How We Estimate Food Debarkation Time With ‘Tensoba’](https://medium.com/gojekengineering/how-we-estimate-food-debarkation-time-with-tensoba-da05674cb758) | 2022 |\n| 148 | Zillow | E-commerce and retail | Extract text features | [Incorporating Listing Descriptions into the Zestimate](https://www.zillow.com/tech/incorporating-listing-descriptions-into-the-zestimate/) | 2022 |\n| 149 | Etsy | E-commerce and retail | Rank marketplace search results | [Deep Learning for Search Ranking at Etsy](https://www.etsy.com/uk/codeascraft/deep-learning-for-search-ranking-at-etsy) | 2022 |\n| 150 | Walmart | E-commerce and retail | Curate e-commerce product recommendations | [Scaling Product Recommendations using Basket Analysis- Part 1](https://medium.com/walmartglobaltech/scaling-product-recommendations-using-basket-analysis-part-1-8434d4f8756f) | 2022 |\n| 151 | Lyft | Delivery and mobility | Optimize trip price | [Pricing at Lyft](https://eng.lyft.com/pricing-at-lyft-8a4022065f8b) | 2022 |\n| 152 | Grammarly | Tech | Correct grammatical errors | [Innovating the Basics: Achieving Superior Precision and Recall in Grammatical Error Correction](https://www.grammarly.com/blog/engineering/innovating-the-basics/) | 2022 |\n| 153 | Twitter | Social platforms | Recommend accounts to follow | [Model-based candidate generation for account recommendations](https://blog.twitter.com/engineering/en_us/topics/insights/2022/model-based-candidate-generation-for-account-recommendations) | 2022 |\n| 154 | Airbnb | Travel,E-commerce and retail | Improve customer travel experience | [Intelligent Automation Platform: Empowering Conversational AI and Beyond at Airbnb](https://medium.com/airbnb-engineering/intelligent-automation-platform-empowering-conversational-ai-and-beyond-at-airbnb-869c44833ff2) | 2022 |\n| 155 | Swiggy | Delivery and mobility | Flag incorrectly captured locations | [Using deep learning to detect dissonance between address text and location](https://bytes.swiggy.com/using-deep-learning-to-detect-dissonance-between-address-text-and-location-4b228bc2c3fb) | 2022 |\n| 156 | Uber | Delivery and mobility | Verify documents | [Uber’s Real-Time Document Check](https://www.uber.com/en-GB/blog/ubers-real-time-document-check/) | 2022 |\n| 157 | Wayfair | E-commerce and retail | Optimize email sending time and frequency | [Nightingale: Scalable Daily Sales Email Sending Decision Model](https://www.aboutwayfair.com/careers/tech-blog/nightingale-scalable-daily-email-sending-decision-model) | 2022 |\n| 158 | Didact AI | Fintech and banking | Predict stock prices | [Didact AI: The anatomy of an ML-powered stock picking engine](https://principiamundi.com/posts/didact-anatomy) | 2022 |\n| 159 | Wayfair | E-commerce and retail | Identify specific entities within a text | [Wayfair’s New Approach to Aspect Based Sentiment Analysis Helps Customers Easily Find “Long Tail” Products](https://www.aboutwayfair.com/careers/tech-blog/wayfairs-new-approach-to-aspect-based-sentiment-analysis-helps-customers-easily-find-long-tail-products) | 2022 |\n| 160 | Oda | Delivery and mobility | Predict driver's non-driving time | [How we went from zero insight to predicting service time with a machine learning model — Part 2/2](https://medium.com/oda-product-tech/how-we-went-from-zero-insight-to-predicting-service-time-with-a-machine-learning-model-part-2-2-ad8b0c3e4838) | 2022 |\n| 161 | Wayfair | E-commerce and retail | Predict intent in customer support messages | [Building Wayfair’s First Virtual Assistant: Automating Customer Service by Text Based Intent Prediction](https://www.aboutwayfair.com/careers/tech-blog/building-wayfairs-first-virtual-assistant-automating-customer-service-by-text-based-intent-prediction) | 2022 |\n| 162 | Linkedin | Social platforms | Estimate the impact of product changes | [Ocelot: Scaling observational causal inference at LinkedIn](https://engineering.linkedin.com/blog/2022/ocelot--scaling-observational-causal-inference-at-linkedin) | 2022 |\n| 163 | Grab | Delivery and mobility,Banking and finance | Detect fraud with graph models | [Graph for fraud detection](https://engineering.grab.com/graph-for-fraud-detection) | 2022 |\n| 164 | Lyft | Delivery and mobility | Make causally valid forecasts | [Causal Forecasting at Lyft (Part 1)](https://eng.lyft.com/causal-forecasting-at-lyft-part-1-14cca6ff3d6d) | 2022 |\n| 165 | Glassdoor | Social platforms | Recommend interesting posts to users | [Personalized Fishbowl Recommendations with Learned Embeddings: Part 2](https://medium.com/glassdoor-engineering/personalized-fishbowl-recommendations-with-learned-embeddings-part-2-78a16b04d396) | 2022 |\n| 166 | Netflix | Media and streaming | Improve video quality at scale | [For your eyes only: improving Netflix video quality with neural networks](https://netflixtechblog.com/for-your-eyes-only-improving-netflix-video-quality-with-neural-networks-5b8d032da09c) | 2022 |\n| 167 | Glassdoor | Social platforms | Recommend interesting posts to users | [Personalized Fishbowl Recommendations with Learned Embeddings: Part 1](https://medium.com/glassdoor-engineering/personalized-fishbowl-recommendations-with-learned-embeddings-part-1-6031abe84661) | 2022 |\n| 168 | Dailymotion | Media and streaming | Recommend diversified video content | [Optimizing video feed recommendations with diversity: Machine Learning first steps](https://medium.com/dailymotion/optimizing-video-feed-recommendations-with-diversity-machine-learning-first-steps-4cf9abdbbffd) | 2022 |\n| 169 | Siemens Healthineers | Tech | Optimize software testing | [Using Machine Learning for Fast Test Feedback to Developers and Test Suite Optimization](https://www.infoq.com/articles/machine-learning-test-feedback-optimization/) | 2022 |\n| 170 | Lyft | Delivery and mobility | Make causally valid forecasts | [Causal Forecasting at Lyft (Part 2)](https://eng.lyft.com/causal-forecasting-at-lyft-part-2-418f1febca5a) | 2022 |\n| 171 | Linkedin | Social platforms | Deliver more relevant job recommendations | [Improving job matching with machine-learned activity features](https://engineering.linkedin.com/blog/2022/improving-job-matching-with-machine-learned-activity-features-) | 2022 |\n| 172 | Cookidoo | E-commerce and retail | Personalize recipe recommendations | [Building A Recipe Recommender System For the Thermomix on Cookidoo – Part 1](https://www.alexanderthamm.com/de/blog/building-a-recipe-recommender-system-for-the-thermomix-on-cookidoo/) | 2022 |\n| 173 | Linkedin | Social platforms | Improve ML model performance with multitask learning | [Applying multitask learning to AI models at LinkedIn](https://engineering.linkedin.com/blog/2022/applying-multitask-learning-to-ai-models-at-linkedin) | 2022 |\n| 174 | Netflix | Media and streaming | Apply causality in experiments and marketing | [A Survey of Causal Inference Applications at Netflix](https://netflixtechblog.com/a-survey-of-causal-inference-applications-at-netflix-b62d25175e6f) | 2022 |\n| 175 | Pinterest | Social platforms | Recommend bids for advertizers | [Advertiser Recommendation Systems at Pinterest](https://medium.com/pinterest-engineering/advertiser-recommendation-systems-at-pinterest-ccb255fbde20) | 2021 |\n| 176 | Grubhub | Delivery and mobility | Forecast volume order | [“I See Tacos In Your Future”: Order Volume Forecasting at Grubhub](https://bytes.grubhub.com/i-see-tacos-in-your-future-order-volume-forecasting-at-grubhub-44d47ad08d5b) | 2021 |\n| 177 | Slack | Tech | Detect spam invites | [Blocking Slack Invite Spam With Machine Learning](https://slack.engineering/blocking-slack-invite-spam-with-machine-learning/) | 2021 |\n| 178 | Faire | E-commerce and retail | Search and navigate marketplace items | [Building Faire’s new marketplace ranking infrastructure](https://craft.faire.com/building-faires-new-marketplace-ranking-infrastructure-a53bf938aba0) | 2021 |\n| 179 | Doordash | E-commerce and retail | Predict delivery supply and demand | [Managing Supply and Demand Balance Through Machine Learning](https://doordash.engineering/2021/06/29/managing-supply-and-demand-balance-through-machine-learning/) | 2021 |\n| 180 | OLX | E-commerce and retail | Recommend e-commerce items | [Item2Vec: Neural Item Embeddings to enhance recommendations](https://tech.olx.com/item2vec-neural-item-embeddings-to-enhance-recommendations-1fd948a6f293) | 2021 |\n| 181 | Dropbox | Tech | Search by image content | [How image search works at Dropbox](https://dropbox.tech/machine-learning/how-image-search-works-at-dropbox) | 2021 |\n| 182 | Scribd | Media and streaming | Extract metadata from documents | [Information Extraction at Scribd](https://tech.scribd.com/blog/2021/information-extraction-at-scribd.html) | 2021 |\n| 183 | Microsoft | Tech | Rank customer support cases | [ML and customer support (Part 1): Using Machine Learning to enable world-class customer support](https://medium.com/data-science-at-microsoft/ml-and-customer-support-part-1-using-machine-learning-to-enable-world-class-customer-support-c90b3b02f6a3) | 2021 |\n| 184 | Stitch Fix | E-commerce and retail | Recommend e-commerce inventory | [Algorithm-Assisted Inventory Curation ](https://multithreaded.stitchfix.com/blog/2021/05/12/algorithm-assisted-inventory-curation/) | 2021 | | |\n| 185 | Twitter | Social platforms | Forecast resource usage and cost | [Forecasting SQL query resource usage with machine learning](https://blog.twitter.com/engineering/en_us/topics/insights/2021/forecasting-sql-query-resource-usage-with-machine-learning) | 2021 |\n| 186 | Google | Tech | Suggest past photos to look at | [A snapshot of AI-powered reminiscing in Google Photos](https://medium.com/people-ai-research/a-snapshot-of-ai-powered-reminiscing-in-google-photos-5a05d2f2aa46) | 2021 |\n| 187 | Uber | Delivery and mobility | Identify cash intermediaries | [Applying Machine Learning in Internal Audit with Sparsely Labeled Data](https://www.uber.com/en-GB/blog/ml-internal-audit/) | 2021 |\n| 188 | Microsoft | Tech | Cluster customer support issues by similarity | [ML and customer support (Part 2): Leveraging topic modeling to identify the top investment areas in support cases](https://medium.com/data-science-at-microsoft/ml-and-customer-support-part-2-leveraging-topic-modeling-to-identify-the-top-investment-areas-in-f0348382c251) | 2021 |\n| 189 | Gousto | Delivery and mobility | Recommend food items and recipes | [Gousto R-series vol 1: Three tales of the Rouxcommender family](https://medium.com/gousto-engineering-techbrunch/gousto-r-series-vol-1-three-tales-of-the-rouxcommender-family-a3555a93edea) | 2021 |\n| 190 | Apple | Tech | Recognize people in photos | [Recognizing People in Photos Through Private On-Device Machine Learning](https://machinelearning.apple.com/research/recognizing-people-photos) | 2021 |\n| 191 | Pinterest | Social platforms | Find lookalike users for ad targeting | [The machine learning behind delivering relevant ads](https://medium.com/pinterest-engineering/the-machine-learning-behind-delivering-relevant-ads-8987fc5ba1c0) | 2021 |\n| 192 | Pinterest | Social platforms | Detect spam users | [Fighting Spam using Clustering and Automated Rule Creation](https://medium.com/pinterest-engineering/fighting-spam-using-clustering-and-automated-rule-creation-1c01d8c11a05) | 2021 |\n| 193 | PayPal | Fintech and banking | Detect payment fraud | [Deploying Large-scale Fraud Detection Machine Learning Models at PayPal](https://medium.com/paypal-tech/machine-learning-model-ci-cd-and-shadow-platform-8c4f44998c78) | 2021 |\n| 194 | Datto | Tech | Predict hard drive failures | [Predicting Hard Drive Failure with Machine Learning](https://datto.engineering/post/predicting-hard-drive-failure-with-machine-learning) | 2021 |\n| 195 | Bumble | Social platforms | Detect rude messages | [Multilingual message content moderation at scale (part 2)](https://medium.com/bumble-tech/multilingual-message-content-moderation-at-scale-7ea562e29e25) | 2021 |\n| 196 | Nextdoor | Social platforms | Send relevant and timely updates | [Nextdoor Notifications: How we use ML to keep neighbors informed](https://engblog.nextdoor.com/nextdoor-notifications-how-we-use-ml-to-keep-neighbors-informed-57d8f707aab0?gi=85c7ad8c8658) | 2021 |\n| 197 | Dropbox | Tech | Identify best time for renewal charge | [Optimizing payments with machine learning](https://dropbox.tech/machine-learning/optimizing-payments-with-machine-learning) | 2021 |\n| 198 | Swiggy | Delivery and mobility | Rank restaurants in search | [Learning To Rank Restaurants](https://bytes.swiggy.com/learning-to-rank-restaurants-c6a69ba4b330) | 2021 |\n| 199 | Brex | Fintech and banking | Classify bank transactions | [How We Built a (Mostly) Automated System to Solve Credit Card Merchant Classification](https://medium.com/brexeng/how-we-built-a-mostly-automated-system-to-solve-credit-card-merchant-classification-f9108029e59b) | 2021 |\n| 200 | Grammarly | Tech | Capture what readers pay attention to | [ATTN: How Grammarly’s NLP/ML Team Figured Out Where Readers Focus in an Email](https://www.grammarly.com/blog/engineering/readers-attention/) | 2021 |\n| 201 | Doordash | Delivery and mobility | Extract information from images | [How DoorDash Quickly Spins Up Multiple Image Recognition Use Cases](https://doordash.engineering/2021/11/03/how-doordash-quickly-spins-up-multiple-image-recognition-use-cases/) | 2021 |\n| 202 | Apple | Tech | Identify best user experience | [Interpretable Adaptive Optimization](https://machinelearning.apple.com/research/interpretable-adaptive-optimization) | 2021 |\n| 203 | Airbnb | Travel,E-commerce and retail | Data privacy and security | [Automating Data Protection at Scale, Part 2](https://medium.com/airbnb-engineering/automating-data-protection-at-scale-part-2-c2b8d2068216) | 2021 |\n| 204 | Capital One | Fintech and banking | Identify suspicious account activity | [How Machine Learning Can Help Fight Money Laundering](https://www.capitalone.com/tech/machine-learning/how-machine-learning-can-help-fight-money-laundering/) | 2021 |\n| 205 | Wayfair | E-commerce and retail | Assign color names to products | [From RGB to Descriptive Color Names: Wayfair's in-house color algorithms to improve customer shopping experience.](https://www.aboutwayfair.com/careers/tech-blog/from-rgb-to-descriptive-color-names-wayfairs-in-house-color-algorithms-to-improve-customer-shopping-experience) | 2021 |\n| 206 | Capital One | Fintech and banking | Automate incident management | [Automated detection, diagnosis & remediation of app failure](https://www.capitalone.com/tech/machine-learning/automated-detection-diagnosis-remediation-of-application-failure/) | 2021 |\n| 207 | Pinterest | Social platforms | Detect policy-violating comments | [How Pinterest powers a healthy comment ecosystem with machine learning](https://medium.com/pinterest-engineering/how-pinterest-powers-a-healthy-comment-ecosystem-with-machine-learning-9e5c3414c8ad) | 2021 |\n| 208 | Spotify | Media and streaming | Personalize homepage content (podcasts, playlist, music) | [The Rise (and Lessons Learned) of ML Models to Personalize Content on Home (Part I)](https://engineering.atspotify.com/2021/11/the-rise-and-lessons-learned-of-ml-models-to-personalize-content-on-home-part-i/) | 2021 |\n| 209 | Stitch Fix | E-commerce and retail | Recommend looks | [Stitching together spaces for query-based recommendations](https://multithreaded.stitchfix.com/blog/2021/08/13/stitching-together-spaces-for-query-based-recommendations/) | 2021 |\n| 210 | Ocado | E-commerce and retail | Forecast e-commerce grocery demand | [Finding the sweet spot](https://careers.ocadogroup.com/blogs/careers-blogs/our-technologies/finding-the-sweet-spot) | 2021 |\n| 211 | Walmart | E-commerce and retail | Categorize e-commerce products | [Deep Learning: Product Categorization and Shelving](https://medium.com/walmartglobaltech/deep-learning-product-categorization-and-shelving-630571e81e96) | 2021 |\n| 212 | Walmart | E-commerce and retail | Recommend learning content | [Mozrt, a Deep Learning Recommendation System Empowering Walmart Store Associates with a Personalized Learning Experience](https://medium.com/walmartglobaltech/mozrt-a-deep-learning-recommendation-system-empowering-walmart-store-associates-with-a-5d42c08d88da) | 2021 |\n| 213 | Walmart | E-commerce and retail | Identify refrigeration defrost | [Predicting Defrost in Refrigeration Cases at Walmart using Fourier Transform](https://medium.com/walmartglobaltech/predicting-defrost-in-refrigeration-cases-at-walmart-using-fourier-transform-e64c0c59323) | 2021 |\n| 214 | New York Times | Media and streaming | Recommend content to read | [Machine Learning and Reader Input Help Us Recommend Articles](https://open.nytimes.com/we-recommend-articles-with-a-little-help-from-our-friends-machine-learning-and-reader-input-e17e85d6cf04) | 2021 |\n| 215 | Mercado Libre | E-commerce and retail | Forecast demand for e-commerce items | [Marketplace Forecasting: Sales or Demand? Why not both? Let’s find out!](https://medium.com/mercadolibre-tech/global-time-series-forecasting-models-for-item-level-demand-and-sales-forecasts-in-our-marketplace-aee2956957ae) | 2021 |\n| 216 | Swiggy | Delivery and mobility | Rank food dishes in search | [Using Deep Learning for Ranking in Dish Search](https://bytes.swiggy.com/using-deep-learning-for-ranking-in-dish-search-4df2772dddce) | 2021 |\n| 217 | PayPal | Fintech and banking | Recommend financial products | [Cross-Selling Optimization Using Deep Learning](https://medium.com/paypal-tech/a-deep-learning-based-approach-to-optimizing-actions-e1ae9d1df152) | 2021 |\n| 218 | Wayfair | E-commerce and retail | Automate ads placement and bidding | [Evolution of Ads Bidding at Wayfair](https://www.aboutwayfair.com/careers/tech-blog/evolution-of-ads-bidding-at-wayfair) | 2021 |\n| 219 | Capital One | Fintech and banking | Improve cardholder experience | [Improving Virtual Card Numbers with Edge Machine Learning](https://www.capitalone.com/tech/machine-learning/edge-machine-learning-eno-virtual-card-numbers/) | 2021 |\n| 220 | Shopify | E-commerce and retail | Categorize e-commerce products | [Using Rich Image and Text Data to Categorize Products at Scale](https://shopify.engineering/using-rich-image-text-data-categorize-products) | 2021 |\n| 221 | Scribd | Media and streaming | Recommend content to read | [Embedding-based Retrieval at Scribd](https://tech.scribd.com/blog/2021/embedding-based-retrieval-scribd.html) | 2021 |\n| 222 | Swiggy | Delivery and mobility | Detect fraud in online food delivery | [DeFraudNet: An End-to-End Weak Supervision Framework to Detect Fraud in Online Food Delivery](https://bytes.swiggy.com/defraudnet-an-end-to-end-weak-supervision-framework-to-detect-fraud-in-online-food-delivery-22366ddce461) | 2021 |\n| 223 | Amazon | E-commerce and retail | Predict coordinates of delivery location | [Using learning-to-rank to precisely locate where to deliver packages](https://www.amazon.science/blog/using-learning-to-rank-to-precisely-locate-where-to-deliver-packages) | 2021 |\n| 224 | PayPal | Fintech and banking | Predict declined transactions | [Using Machine Learning to Improve Payment Authorization Rate](https://medium.com/paypal-tech/using-machine-learning-to-improve-payment-authorization-rates-bc3b2cbf4999) | 2021 |\n| 225 | Stripe | Fintech and banking | Detect fraud in online payments | [A primer on machine learning for fraud detection](https://stripe.com/en-mx/guides/primer-on-machine-learning-for-fraud-protection) | 2021 |\n| 226 | Slack | Tech | Predict Slack connect invites | [Email Classification](https://slack.engineering/email-classification/) | 2021 |\n| 227 | Wayfair | E-commerce and retail | Recommend furniture items | [MARS: Transformer Networks for Sequential Recommendation](https://www.aboutwayfair.com/careers/tech-blog/mars-transformer-networks-for-sequential-recommendation) | 2021 |\n| 228 | Grammarly | Tech | Detect grammatical errors | [Grammatical Error Correction: Tag, Not Rewrite](https://www.grammarly.com/blog/engineering/gec-tag-not-rewrite/) | 2021 |\n| 229 | Nordstrom | E-commerce and retail | Generate outfit combinations | [AI-Created Outfits](https://medium.com/tech-at-nordstrom/ai-created-outfits-9529300a1af3) | 2021 |\n| 230 | Doordash | Delivery and mobility | Deliver orders on time | [Using ML and Optimization to Solve DoorDash’s Dispatch Problem](https://doordash.engineering/2021/08/17/using-ml-and-optimization-to-solve-doordashs-dispatch-problem/) | 2021 |\n| 231 | Zillow | E-commerce and retail | Recommend similar homes | [Improving Recommendation Quality by Tapping into Listing Text](https://www.zillow.com/tech/improve-quality-listing-text/) | 2021 |\n| 232 | Lifen | Tech | Recognize PDF layout | [Fast graph-based layout detection](https://medium.com/lifen-engineering/fast-graph-based-layout-detection-19fc7ab11b17) | 2021 |\n| 233 | PayPal | Fintech and banking | Prevent repeated payment fraud | [How PayPal Uses Real-time Graph Database and Graph Analysis to Fight Fraud](https://medium.com/paypal-tech/how-paypal-uses-real-time-graph-database-and-graph-analysis-to-fight-fraud-96a2b918619a) | 2021 |\n| 234 | Bumble | Social platforms | Detect rude messages | [Multilingual message content moderation at scale (part 1)](https://medium.com/bumble-tech/multilingual-message-content-moderation-at-scale-ddd0da1e23ed) | 2021 |\n| 235 | Spotify | Media and streaming | Personalize homepage content (podcasts, playlist, music) | [The Rise (and Lessons Learned) of ML Models to Personalize Content on Home (Part II)](https://engineering.atspotify.com/2021/11/the-rise-and-lessons-learned-of-ml-models-to-personalize-content-on-home-part-ii/) | 2021 |\n| 236 | Swiggy | Delivery and mobility | Estimate travel distance | [Learning to Predict Two-Wheeler Travel Distance](https://bytes.swiggy.com/learning-to-predict-two-wheeler-travel-distance-752d836d741d) | 2021 |\n| 237 | Expedia | Travel,E-commerce and retail | Personalize travel search results | [Personalized Ranking Model for Lodging](https://medium.com/expedia-group-tech/personalized-ranking-model-for-lodging-5be43ae975fe) | 2021 |\n| 238 | Scribd | Media and streaming | Classify documents | [Categorizing user-uploaded documents](https://tech.scribd.com/blog/2021/categorizing-user-uploaded-documents.html) | 2021 |\n| 239 | Meta | Social platforms | Personalize the newsfeed content | [How machine learning powers Facebook’s News Feed ranking](https://engineering.fb.com/2021/01/26/ml-applications/news-feed-ranking/) | 2021 |\n| 240 | Google | Tech | Correct grammatical errors | [Grammar Correction as You Type, on Pixel 6](https://ai.googleblog.com/2021/10/grammar-correction-as-you-type-on-pixel.html) | 2021 |\n| 241 | Nubank | Fintech and banking | Predict conversions and attract new customers | [Beyond prediction machines](https://building.nubank.com.br/beyond-prediction-machines/) | 2021 |\n| 242 | Grammarly | Tech | Correct grammatical errors | [Adversarial Grammatical Error Correction](https://www.grammarly.com/blog/engineering/adversarial-grammatical-error-correction) | 2021 |\n| 243 | Scribd | Media and streaming | Classify user-uploaded documents | [Identifying Document Types at Scribd](https://tech.scribd.com/blog/2021/identifying-document-types.html) | 2021 |\n| 244 | Oda | Delivery and mobility | Predict driver's non-driving time | [How we went from zero insight to predicting service time with a machine learning model — Part 1](https://medium.com/oda-product-tech/how-we-went-from-zero-insight-to-predicting-service-time-with-a-machine-learning-model-part-1-516b9545d02f) | 2021 |\n| 245 | Mercado Libre | E-commerce and retail | Predict customer engagement and LTV | [Causal Inference — Estimating Long-term Engagement](https://medium.com/mercadolibre-tech/causal-inference-estimating-long-term-engagement-fac517929073) | 2021 |\n| 246 | Dailymotion | Media and streaming | Target contextual advertising | [How Deep Learning can boost Contextual Advertising Capabilities](https://medium.com/dailymotion/how-deep-learning-can-boost-contextual-advertising-capabilities-c9ca7c8fc4e9) | 2021 |\n| 247 | Wayfair | E-commerce and retail | Optimize digital ads | [Building Scalable and Performant Marketing ML Systems at Wayfair](https://www.aboutwayfair.com/careers/tech-blog/building-scalable-and-performant-marketing-ml-systems-at-wayfair) | 2021 |\n| 248 | Wayfair | E-commerce and retail | Show relevant content to new customers | [Share of Voice Optimization Engine](https://www.aboutwayfair.com/careers/tech-blog/share-of-voice-optimization-engine) | 2021 |\n| 249 | Wayfair | E-commerce and retail | Optimize paid media marketing | [Contextual Bandit for Marketing Treatment Optimization](https://www.aboutwayfair.com/careers/tech-blog/contextual-bandit-for-marketing-treatment-optimization) | 2021 |\n| 250 | Microsoft | Tech | Classify cloud workload types | [How we used ML — and heuristic data labeling — to help customers with their cloud migration](https://medium.com/data-science-at-microsoft/how-we-used-ml-and-heuristic-data-labeling-to-help-customers-with-their-cloud-migration-d3af7ff020fc) | 2021 |\n| 251 | Github | Tech | Help users find contribution opportunities | [How we built the good first issues feature](https://github.blog/2020-01-22-how-we-built-good-first-issues/) | 2020 |\n| 252 | Linkedin | Social platforms | Serve personalized learning recommendations | [A closer look at the AI behind course recommendations on LinkedIn Learning, Part 1](https://engineering.linkedin.com/blog/2020/course-recommendations-ai-part-one) | 2020 |\n| 253 | Bumble | Social platforms | Derive information from images | [Image detection as a service](https://medium.com/bumble-tech/image-detection-as-a-service-9bd463f74f43) | 2020 |\n| 254 | Gojek | Delivery and mobility | Generate names for pickup points | [How Gojek Uses NLP to Name Pickup Locations at Scale](https://www.gojek.io/blog/nlp-cartobert) | 2020 |\n| 255 | Mozilla | Tech | Predict the outcome of software tests | [Testing Firefox more efficiently with machine learning](https://hacks.mozilla.org/2020/07/testing-firefox-more-efficiently-with-machine-learning/) | 2020 |\n| 256 | Adyen | Fintech and banking | Predict probability of transaction success | [Optimizing payment conversion rates with contextual multi-armed bandits](https://www.adyen.com/blog/optimizing-payment-conversion-rates-with-contextual-multi-armed-bandits) | 2020 |\n| 257 | Wayfair | E-commerce and retail | Detect payment fraud | [Explainable Fraud Detection](https://www.aboutwayfair.com/tech-innovation/explainable-fraud-detection) | 2020 |\n| 258 | Lyft | Delivery and mobility | Provide location suggestions | [How Lyft predicts a rider’s destination for better in-app experience](https://eng.lyft.com/how-lyft-predicts-your-destination-with-attention-791146b0a439) | 2020 |\n| 259 | Zillow | E-commerce and retail | Generate floor plans from photos | [Zillow Floor Plan: Training Models to Detect Windows, Doors and Openings in Panoramas](https://www.zillow.com/tech/training-models-to-detect-windows-doors-in-panos/) | 2020 |\n| 260 | Linkedin | Social platforms | Serve personalized learning recommendations | [A closer look at the AI behind course recommendations on LinkedIn Learning, Part 2](https://engineering.linkedin.com/blog/2020/course-recommendations-ai-part-two) | 2020 |\n| 261 | Doordash | Delivery and mobility | Optimize marketing spending | [Optimizing DoorDash’s Marketing Spend with Machine Learning](https://doordash.engineering/2020/07/31/optimizing-marketing-spend-with-ml/) | 2020 |\n| 262 | Etsy | E-commerce and retail | Personalize e-commerce search | [Bringing Personalized Search to Etsy](https://www.etsy.com/codeascraft/bringing-personalized-search-to-etsy/) | 2020 |\n| 263 | Airbnb | Travel,E-commerce and retail | Rank travel search results | [Improving Deep Learning for Ranking Stays at Airbnb](https://medium.com/airbnb-engineering/improving-deep-learning-for-ranking-stays-at-airbnb-959097638bde) | 2020 |\n| 264 | Wayfair | E-commerce and retail | Improve search experience for new customers | [Bayesian Product Ranking at Wayfair ](https://www.aboutwayfair.com/tech-innovation/bayesian-product-ranking-at-wayfair) | 2020 | | |\n| 265 | Twitter | Social platforms | Predict value of ad requests | [Using machine learning to predict the value of ad requests](https://blog.twitter.com/engineering/en_us/topics/insights/2020/using-machine-learning-to-predict-the-value-of-ad-requests) | 2020 |\n| 266 | Zynga | Gaming | Personalize push notification timing | [Deep Reinforcement Learning in Production Part 2: Personalizing User Notifications](https://towardsdatascience.com/deep-reinforcement-learning-in-production-part-2-personalizing-user-notifications-812a68ce2355) | 2020 |\n| 267 | Zillow | E-commerce and retail | Rank homes to buy | [Guided Search — Personalized Search Refinements to Help Customers Find their Dream Home](https://www.zillow.com/tech/personalized-search-refinements/ ) | 2020 |\n| 268 | Picnic | Delivery and mobility | Predict delivery drop times | [Optimal drop times using machine learning](https://blog.picnic.nl/the-trade-off-between-efficiency-and-being-on-time-optimizing-drop-times-using-machine-learning-d3f6fb1b0f31) | 2020 |\n| 269 | Shopify | E-commerce and retail | Categorize e-commerce products | [Categorizing Products at Scale](https://shopify.engineering/categorizing-products-at-scale) | 2020 |\n| 270 | Gojek | Delivery and mobility | Target cross-sell to existing users | [How We Built a Matchmaking Algorithm to Cross-Sell Products](https://www.gojek.io/blog/how-we-built-a-matchmaking-algorithm-to-cross-sell-products) | 2020 |\n| 271 | PayPal | Fintech and banking | Detect payment fraud | [Multi-Domain Fraud Detection While Reducing Good User Declines](https://medium.com/paypal-tech/multi-domain-fraud-detection-while-reducing-good-user-declines-part-i-e8bba5b07da8) | 2020 |\n| 272 | OLX | E-commerce and retail | Detect stolen photos | [Fighting fraud with Triplet Loss](https://tech.olx.com/fighting-fraud-with-triplet-loss-86e5f79c7a3e) | 2020 |\n| 273 | Stripe | Fintech and banking | Detect fraud in online payments | [Similarity clustering to catch fraud rings](https://stripe.com/blog/similarity-clustering) | 2020 |\n| 274 | Doordash | Delivery and mobility | Search for restaurants and dishes | [Things Not Strings: Understanding Search Intent with Better Recall](https://doordash.engineering/2020/12/15/understanding-search-intent-with-better-recall/) | 2020 |\n| 275 | Spotify | Media and streaming | Recommend shortcuts for homepage | [Reach for the Top: How Spotify Built Shortcuts in Just Six Months](https://engineering.atspotify.com/2020/04/reach-for-the-top-how-spotify-built-shortcuts-in-just-six-months/) | 2020 |\n| 276 | Wayfair | E-commerce and retail | Recommend complementary products | [The Visual Complements Model (ViCs): Complementary Product Recommendations From Visual Cues](https://www.aboutwayfair.com/tech-innovation/the-visual-complements-model-vics-complementary-product-recommendations-from-visual-cues) | 2020 |\n| 277 | Dailymotion | Media and streaming | Automatically categorize videos | [How we used Cross-Lingual Transfer Learning to categorize our content](https://medium.com/dailymotion/how-we-used-cross-lingual-transfer-learning-to-categorize-our-content-c8e0f9c1c6c3) | 2020 |\n| 278 | Duolingo | Tech | Teaching foreign languages | [How Duolingo uses AI in every part of its app](https://venturebeat.com/ai/how-duolingo-uses-ai-in-every-part-of-its-app/) | 2020 |\n| 279 | Firefox | Tech | Automatically assign new untriaged bugs | [Teaching machines to triage Firefox bugs](https://hacks.mozilla.org/2019/04/teaching-machines-to-triage-firefox-bugs/) | 2019 |\n| 280 | Dropbox | Tech | Predict files users search for | [Using machine learning to predict what file you need next](https://dropbox.tech/machine-learning/content-suggestions-machine-learning) | 2019 |\n| 281 | Zoominfo | Tech | Predict data accuracy | [Using Machine Learning to Determine Contact Accuracy Scores](https://engineering.zoominfo.com/machine-learning-accuracy-scores) | 2019 |\n| 282 | Airbnb | Travel,E-commerce and retail | Recommend marketplace items | [Machine Learning-Powered Search Ranking of Airbnb Experiences](https://medium.com/airbnb-engineering/machine-learning-powered-search-ranking-of-airbnb-experiences-110b4b1a0789) | 2019 |\n| 283 | Lyft | Delivery and mobility | Predict location of traffic control elements | [Detecting Stop Signs and Traffic Signals: Deep Learning at Lyft Mapping](https://eng.lyft.com/detecting-stop-signs-and-traffic-signals-deep-learning-at-lyft-mapping-75bac609c231) | 2019 |\n| 284 | Gojek | Delivery and mobility | Personalize search results | [The Secret Sauce Behind Search Personalisation](https://www.gojek.io/blog/the-secret-sauce-behind-search-personalisation) | 2019 |\n| 285 | Instacart | Delivery and mobility | Spot lost demand | [Modeling the unseen](https://tech.instacart.com/modeling-the-unseen-6a51c9a02430) | 2019 |\n| 286 | Apple | Tech | Identify text language | [Language Identification from Very Short Strings](https://machinelearning.apple.com/research/language-identification-from-very-short-strings) | 2019 |\n| 287 | Stitch Fix | E-commerce and retail | Extract information from customer notes | [Give Me Jeans not Shoes: How BERT Helps Us Deliver What Clients Want](https://multithreaded.stitchfix.com/blog/2019/07/15/give-me-jeans/) | 2019 |\n| 288 | Lyft | Delivery and mobility | Detect errors in maps | [How Lyft Creates Hyper-Accurate Maps from Open-Source Maps and Real-Time Data](https://eng.lyft.com/how-lyft-creates-hyper-accurate-maps-from-open-source-maps-and-real-time-data-8dcf9abdd46a) | 2019 |\n| 289 | King | Gaming | Automate playtesting pipeline | [Human-Like Playtesting with Deep Learning](https://medium.com/techking/human-like-playtesting-with-deep-learning-92adafffe921) | 2019 |\n| 290 | Gojek | Delivery and mobility | Analyse the relevance of search results | [Is This What You Were Looking For?](https://www.gojek.io/blog/is-this-what-you-were-looking-for) | 2019 |\n| 291 | Lyft | Delivery and mobility | Build a marketing automation platform | [Building Lyft’s Marketing Automation Platform](https://eng.lyft.com/lyft-marketing-automation-b43b7b7537cc) | 2019 |\n| 292 | Wayfair | E-commerce and retail | Model uplift | [Modeling Uplift Directly: Uplift Decision Tree with KL Divergence and Euclidean Distance as Splitting Criteria](https://www.aboutwayfair.com/tech-innovation/modeling-uplift-directly-uplift-decision-tree-with-kl-divergence-and-euclidean-distance-as-splitting-criteria) | 2019 |\n| 293 | Gojek | Delivery and mobility | Accurately forecast demand | [Under the Hood of Gojek’s Automated Forecasting Tool](https://www.gojek.io/blog/under-the-hood-of-gojeks-automated-forecasting-tool) | 2019 |\n| 294 | Lyft | Delivery and mobility | Predict rides and driver hours | [Making cohort-based long-term forecasts at Lyft](https://eng.lyft.com/making-long-term-forecasts-at-lyft-fac475b3ba52) | 2019 |\n| 295 | Lyft | Delivery and mobility | Predict fraudulent activity | [Fingerprinting fraudulent behavior](https://eng.lyft.com/fingerprinting-fraudulent-behavior-6663d0264fad) | 2018 |\n| 296 | Netflix | Media and streaming | Improve streaming quality | [Using Machine Learning to Improve Streaming Quality at Netflix](https://netflixtechblog.com/using-machine-learning-to-improve-streaming-quality-at-netflix-9651263ef09f) | 2018 |\n| 297 | Lyft | Delivery and mobility | Identify user fraud | [From shallow to deep learning in fraud](https://eng.lyft.com/from-shallow-to-deep-learning-in-fraud-9dafcbcef743?gi=6e6a315e3f92) | 2018 |\n| 298 | Instacart | E-commerce and retail | Predict grocery item availability | [Predicting the real-time availability of 200 million grocery items](https://tech.instacart.com/predicting-real-time-availability-of-200-million-grocery-items-in-us-canada-stores-61f43a16eafe) | 2018 |\n| 299 | Lyft | Delivery and mobility | Personalize marketing offers | [Empowering personalized marketing with machine learning](https://eng.lyft.com/empowering-personalized-marketing-with-machine-learning-fd36e6bdeca6) | 2018 |\n| 300 | Instacart | E-commerce and retail | Optimize food delivery logistics | [Space, Time and Groceries](https://tech.instacart.com/space-time-and-groceries-a315925acf3a) | 2017 |\n| 301 | Airbnb | Travel,E-commerce and retail | Predict Value of Homes | [Using Machine Learning to Predict Value of Homes On Airbnb](https://medium.com/airbnb-engineering/using-machine-learning-to-predict-value-of-homes-on-airbnb-9272d3d4739d) | 2017 |\n| 302 | Netflix | Media and streaming | Improve Streamning Quality | [Using Machine Learning to Improve Streaming Quality at Netflix](https://medium.com/netflix-techblog/using-machine-learning-to-improve-streaming-quality-at-netflix-9651263ef09f) | 2018 |\n| 303 | Booking.com | Travel,E-commerce and retail | 150 Successful Machine Learning Models | [150 Successful Machine Learning Models: 6 Lessons Learned at Booking.com](https://blog.acolyer.org/2019/10/07/150-successful-machine-learning-models/) | 2019 |\n| 304 | Chicisimo | Fashion and retail | Grow User base using vertical ML approch | [How we grew from 0 to 4 million women on our fashion app, with a vertical machine learning approach](https://medium.com/hackernoon/how-we-grew-from-0-to-4-million-women-on-our-fashion-app-with-a-vertical-machine-learning-approach-f8b7fc0a89d7) | 2019 |\n| 305 | Airbnb | Travel,E-commerce and retail | ML Powered search ranking | [Machine Learning-Powered Search Ranking of Airbnb Experiences](https://medium.com/airbnb-engineering/machine-learning-powered-search-ranking-of-airbnb-experiences-110b4b1a0789) | 2019 |\n| 306 | Lyft | Delivery and mobility | Shallow to deep learning in fraud | [From shallow to deep learning in fraud](https://eng.lyft.com/from-shallow-to-deep-learning-in-fraud-9dafcbcef743) | 2018 |\n| 307 | Uber | Delivery and mobility | 100+ Petabytes with Minute Latency | [Uber's Big Data Platform: 100+ Petabytes with Minute Latency](https://eng.uber.com/uber-big-data-platform/) | 2018 |\n| 308 | Dropbox | Tech | Modern OCR with CV and DL | [Creating a Modern OCR Pipeline Using Computer Vision and Deep Learning](https://blogs.dropbox.com/tech/2017/04/creating-a-modern-ocr-pipeline-using-computer-vision-and-deep-learning/) | 2017 |\n| 309 | Uber | Tech | Scaling ML with Michelangelo | [Scaling Machine Learning at Uber with Michelangelo](https://eng.uber.com/scaling-michelangelo/) | 2019 |\n\n\n> For more information, visit [Evidently AI - ML System Design](https://www.evidentlyai.com/ml-system-design) and [ML Systems Design](https://huyenchip.com/machine-learning-systems-design/case-studies.html)\n\n## Star History\n\n[![Star History Chart](https://api.star-history.com/svg?repos=Engineer1999/A-Curated-List-of-ML-System-Design-Case-Studies&type=Date)](https://www.star-history.com/#Engineer1999/A-Curated-List-of-ML-System-Design-Case-Studies&Date)\n" } ]