gitextract_laoqm0uq/

├── LICENSE
├── README.md
├── chapter02_mathematical-building-blocks.ipynb
├── chapter03_introduction-to-ml-frameworks.ipynb
├── chapter04_classification-and-regression.ipynb
├── chapter05_fundamentals-of-ml.ipynb
├── chapter07_deep-dive-keras.ipynb
├── chapter08_image-classification.ipynb
├── chapter09_convnet-architecture-patterns.ipynb
├── chapter10_interpreting-what-convnets-learn.ipynb
├── chapter11_image-segmentation.ipynb
├── chapter12_object-detection.ipynb
├── chapter13_timeseries-forecasting.ipynb
├── chapter14_text-classification.ipynb
├── chapter15_language-models-and-the-transformer.ipynb
├── chapter16_text-generation.ipynb
├── chapter17_image-generation.ipynb
├── chapter18_best-practices-for-the-real-world.ipynb
├── first_edition/
│   ├── 2.1-a-first-look-at-a-neural-network.ipynb
│   ├── 3.5-classifying-movie-reviews.ipynb
│   ├── 3.6-classifying-newswires.ipynb
│   ├── 3.7-predicting-house-prices.ipynb
│   ├── 4.4-overfitting-and-underfitting.ipynb
│   ├── 5.1-introduction-to-convnets.ipynb
│   ├── 5.2-using-convnets-with-small-datasets.ipynb
│   ├── 5.3-using-a-pretrained-convnet.ipynb
│   ├── 5.4-visualizing-what-convnets-learn.ipynb
│   ├── 6.1-one-hot-encoding-of-words-or-characters.ipynb
│   ├── 6.1-using-word-embeddings.ipynb
│   ├── 6.2-understanding-recurrent-neural-networks.ipynb
│   ├── 6.3-advanced-usage-of-recurrent-neural-networks.ipynb
│   ├── 6.4-sequence-processing-with-convnets.ipynb
│   ├── 8.1-text-generation-with-lstm.ipynb
│   ├── 8.2-deep-dream.ipynb
│   ├── 8.3-neural-style-transfer.ipynb
│   ├── 8.4-generating-images-with-vaes.ipynb
│   └── 8.5-introduction-to-gans.ipynb
└── second_edition/
    ├── README.md
    ├── chapter02_mathematical-building-blocks.ipynb
    ├── chapter03_introduction-to-keras-and-tf.ipynb
    ├── chapter04_getting-started-with-neural-networks.ipynb
    ├── chapter05_fundamentals-of-ml.ipynb
    ├── chapter07_working-with-keras.ipynb
    ├── chapter08_intro-to-dl-for-computer-vision.ipynb
    ├── chapter09_part01_image-segmentation.ipynb
    ├── chapter09_part02_modern-convnet-architecture-patterns.ipynb
    ├── chapter09_part03_interpreting-what-convnets-learn.ipynb
    ├── chapter10_dl-for-timeseries.ipynb
    ├── chapter11_part01_introduction.ipynb
    ├── chapter11_part02_sequence-models.ipynb
    ├── chapter11_part03_transformer.ipynb
    ├── chapter11_part04_sequence-to-sequence-learning.ipynb
    ├── chapter12_part01_text-generation.ipynb
    ├── chapter12_part02_deep-dream.ipynb
    ├── chapter12_part03_neural-style-transfer.ipynb
    ├── chapter12_part04_variational-autoencoders.ipynb
    ├── chapter12_part05_gans.ipynb
    ├── chapter13_best-practices-for-the-real-world.ipynb
    └── chapter14_conclusions.ipynb