SYMBOL INDEX (355 symbols across 46 files)

FILE: Course-1-Supervised-Machine-Learning-Regression-and-Classification/Course-1-Week-1/Course-1-Week-1-Optional-Labs/lab_utils_common.py
  function compute_cost_matrix (line 20) | def compute_cost_matrix(X, y, w, b, verbose=False):
  function compute_gradient_matrix (line 44) | def compute_gradient_matrix(X, y, w, b):
  function compute_cost (line 68) | def compute_cost(X, y, w, b):
  function compute_gradient (line 87) | def compute_gradient(X, y, w, b):

FILE: Course-1-Supervised-Machine-Learning-Regression-and-Classification/Course-1-Week-1/Course-1-Week-1-Optional-Labs/lab_utils_uni.py
  function plt_house_x (line 23) | def plt_house_x(X, y,f_wb=None, ax=None):
  function mk_cost_lines (line 37) | def mk_cost_lines(x,y,w,b, ax):
  function plt_intuition (line 66) | def plt_intuition(x_train, y_train):
  function plt_stationary (line 100) | def plt_stationary(x_train, y_train):
  class plt_update_onclick (line 162) | class plt_update_onclick:
    method __init__ (line 163) | def __init__(self, fig, ax, x_train,y_train, dyn_items):
    method __call__ (line 171) | def __call__(self, event):
  function soup_bowl (line 200) | def soup_bowl():
  function inbounds (line 239) | def inbounds(a,b,xlim,ylim):
  function plt_contour_wgrad (line 249) | def plt_contour_wgrad(x, y, hist, ax, w_range=[-100, 500, 5], b_range=[-...
  function plt_divergence (line 279) | def plt_divergence(p_hist, J_hist, x_train,y_train):
  function add_line (line 341) | def add_line(dj_dx, x1, y1, d, ax):
  function plt_gradients (line 353) | def plt_gradients(x_train,y_train, f_compute_cost, f_compute_gradient):

FILE: Course-1-Supervised-Machine-Learning-Regression-and-Classification/Course-1-Week-2/Course-1-Week-2-Optional-Labs/lab_utils_common.py
  function compute_cost_matrix (line 20) | def compute_cost_matrix(X, y, w, b, verbose=False):
  function compute_gradient_matrix (line 44) | def compute_gradient_matrix(X, y, w, b):
  function compute_cost (line 68) | def compute_cost(X, y, w, b):
  function compute_gradient (line 87) | def compute_gradient(X, y, w, b):

FILE: Course-1-Supervised-Machine-Learning-Regression-and-Classification/Course-1-Week-2/Course-1-Week-2-Optional-Labs/lab_utils_multi.py
  function load_data_multi (line 11) | def load_data_multi():
  function plt_house_x (line 21) | def plt_house_x(X, y,f_wb=None, ax=None):
  function mk_cost_lines (line 35) | def mk_cost_lines(x,y,w,b, ax):
  function inbounds (line 56) | def inbounds(a,b,xlim,ylim):
  function plt_contour_wgrad (line 68) | def plt_contour_wgrad(x, y, hist, ax, w_range=[-100, 500, 5], b_range=[-...
  function plt_contour_multi (line 100) | def plt_contour_multi(x, y, w, b, ax, prange, p1, p2, title="", xlabel="...
  function plt_equal_scale (line 122) | def plt_equal_scale(X_train, X_norm, y_train):
  function plt_divergence (line 151) | def plt_divergence(p_hist, J_hist, x_train,y_train):
  function add_line (line 213) | def add_line(dj_dx, x1, y1, d, ax):
  function plt_gradients (line 225) | def plt_gradients(x_train,y_train, f_compute_cost, f_compute_gradient):
  function norm_plot (line 272) | def norm_plot(ax, data):
  function plot_cost_i_w (line 287) | def plot_cost_i_w(X,y,hist):
  function compute_gradient_matrix (line 306) | def compute_gradient_matrix(X, y, w, b):
  function compute_cost_matrix (line 329) | def compute_cost_matrix(X, y, w, b, verbose=False):
  function compute_cost (line 354) | def compute_cost(X, y, w, b):
  function compute_gradient (line 372) | def compute_gradient(X, y, w, b):
  function gradient_descent_houses (line 399) | def gradient_descent_houses(X, y, w_in, b_in, cost_function, gradient_fu...
  function run_gradient_descent (line 458) | def run_gradient_descent(X,y,iterations=1000, alpha = 1e-6):
  function run_gradient_descent_feng (line 479) | def run_gradient_descent_feng(X,y,iterations=1000, alpha = 1e-6):
  function gradient_descent (line 491) | def gradient_descent(X, y, w_in, b_in, cost_function, gradient_function,...
  function load_house_data (line 546) | def load_house_data():
  function zscore_normalize_features (line 552) | def zscore_normalize_features(X,rtn_ms=False):

FILE: Course-1-Supervised-Machine-Learning-Regression-and-Classification/Course-1-Week-2/Course-1-Week-2-Practice-Labs/public_tests.py
  function compute_cost_test (line 3) | def compute_cost_test(target):
  function compute_gradient_test (line 43) | def compute_gradient_test(target):

FILE: Course-1-Supervised-Machine-Learning-Regression-and-Classification/Course-1-Week-2/Course-1-Week-2-Practice-Labs/utils.py
  function load_data (line 3) | def load_data():
  function load_data_multi (line 9) | def load_data_multi():

FILE: Course-1-Supervised-Machine-Learning-Regression-and-Classification/Course-1-Week-3/Course-1-Week-3-Optional-Labs/lab_utils_common.py
  function sigmoid (line 23) | def sigmoid(z):
  function predict_logistic (line 46) | def predict_logistic(X, w, b):
  function predict_linear (line 50) | def predict_linear(X, w, b):
  function compute_cost_logistic (line 54) | def compute_cost_logistic(X, y, w, b, lambda_=0, safe=False):
  function log_1pexp (line 89) | def log_1pexp(x, maximum=20):
  function compute_cost_matrix (line 106) | def compute_cost_matrix(X, y, w, b, logistic=False, lambda_=0, safe=True):
  function compute_gradient_matrix (line 140) | def compute_gradient_matrix(X, y, w, b, logistic=False, lambda_=0):
  function gradient_descent (line 168) | def gradient_descent(X, y, w_in, b_in, alpha, num_iters, logistic=False,...
  function zscore_normalize_features (line 213) | def zscore_normalize_features(X):
  function plot_data (line 243) | def plot_data(X, y, ax, pos_label="y=1", neg_label="y=0", s=80, loc='bes...
  function plt_tumor_data (line 260) | def plt_tumor_data(x, y, ax):
  function draw_vthresh (line 277) | def draw_vthresh(ax,x):

FILE: Course-1-Supervised-Machine-Learning-Regression-and-Classification/Course-1-Week-3/Course-1-Week-3-Optional-Labs/plt_logistic_loss.py
  function compute_cost_logistic_sq_err (line 8) | def compute_cost_logistic_sq_err(X, y, w, b):
  function plt_logistic_squared_error (line 27) | def plt_logistic_squared_error(X,y):
  function plt_logistic_cost (line 55) | def plt_logistic_cost(X,y):
  function soup_bowl (line 98) | def soup_bowl():
  function plt_simple_example (line 142) | def plt_simple_example(x, y):
  function plt_two_logistic_loss_curves (line 161) | def plt_two_logistic_loss_curves():

FILE: Course-1-Supervised-Machine-Learning-Regression-and-Classification/Course-1-Week-3/Course-1-Week-3-Optional-Labs/plt_one_addpt_onclick.py
  class plt_one_addpt_onclick (line 12) | class plt_one_addpt_onclick:
    method __init__ (line 14) | def __init__(self, x, y, w, b, logistic=True):
    method add_data (line 69) | def add_data(self, event):
    method calc_linear (line 85) | def calc_linear(self, event):
    method calc_logistic (line 104) | def calc_logistic(self, event):
    method thresh (line 130) | def thresh(self, event):
    method draw_thresh (line 138) | def draw_thresh(self):
    method remove_thresh (line 164) | def remove_thresh(self):
    method resize_sq (line 170) | def resize_sq(self, bcid):

FILE: Course-1-Supervised-Machine-Learning-Regression-and-Classification/Course-1-Week-3/Course-1-Week-3-Optional-Labs/plt_overfit.py
  function map_one_feature (line 12) | def map_one_feature(X1, degree):
  function map_feature (line 28) | def map_feature(X1, X2, degree):
  function munge (line 46) | def munge(base, exp):
  function plot_decision_boundary (line 53) | def plot_decision_boundary(ax, x0r,x1r, predict,  w, b, scaler = False, ...
  function plot_decision_boundary_sklearn (line 82) | def plot_decision_boundary_sklearn(x0r, x1r, predict, degree,  scaler = ...
  class button_manager (line 119) | class button_manager:
    method __init__ (line 129) | def __init__(self,fig, dim, labels, init, call_on_click):
    method reinit (line 145) | def reinit(self):
    method button_click (line 150) | def button_click(self, event):
  class overfit_example (line 161) | class overfit_example():
    method __init__ (line 167) | def __init__(self, regularize=False):
    method updt_lambda (line 212) | def updt_lambda(self, idx, firsttime=False):
    method toggle_type (line 216) | def toggle_type(self, idx, firsttime=False):
    method logistic_data (line 227) | def logistic_data(self,redraw=False):
    method linear_data (line 249) | def linear_data(self,redraw=False):
    method add_data (line 279) | def add_data(self, event):
    method add_data_logistic (line 286) | def add_data_logistic(self, event):
    method add_data_linear (line 301) | def add_data_linear(self, event):
    method fitdata_clicked (line 321) | def fitdata_clicked(self,event):
    method linear_regression (line 327) | def linear_regression(self):
    method logistic_regression (line 351) | def logistic_regression(self):
    method update_equation (line 375) | def update_equation(self, idx, firsttime=False):

FILE: Course-1-Supervised-Machine-Learning-Regression-and-Classification/Course-1-Week-3/Course-1-Week-3-Optional-Labs/plt_quad_logistic.py
  class plt_quad_logistic (line 19) | class plt_quad_logistic:
    method __init__ (line 25) | def __init__(self, x_train,y_train, w_range, b_range):
    method click_contour (line 61) | def click_contour(self, event):
    method calc_logistic (line 75) | def calc_logistic(self, event):
  class data_plot (line 91) | class data_plot:
    method __init__ (line 95) | def __init__(self, ax, x_train, y_train, w, b):
    method plt_tumor_data (line 109) | def plt_tumor_data(self):
    method update (line 122) | def update(self, w, b):
    method draw_logistic_lines (line 128) | def draw_logistic_lines(self, firsttime=False):
    method mk_cost_lines (line 144) | def mk_cost_lines(self, firsttime=False):
  class contour_and_surface_plot (line 176) | class contour_and_surface_plot:
    method __init__ (line 180) | def __init__(self, axc, axs, x_train, y_train, w_range, b_range, w, b):
    method update_contour_wb_lines (line 229) | def update_contour_wb_lines(self, w, b, firsttime=False):
  class cost_plot (line 250) | class cost_plot:
    method __init__ (line 254) | def __init__(self,ax):
    method re_init (line 261) | def re_init(self):
    method add_cost (line 265) | def add_cost(self,J_hist):
  class path (line 270) | class path:
    method __init__ (line 274) | def __init__(self, w, b, ax):
    method re_init (line 281) | def re_init(self, w, b):
    method add_path_item (line 288) | def add_path_item(self, w, b):
  function truncate_colormap (line 302) | def truncate_colormap(cmap, minval=0.0, maxval=1.0, n=100):
  function plt_prob (line 309) | def plt_prob(ax, w_out,b_out):

FILE: Course-1-Supervised-Machine-Learning-Regression-and-Classification/Course-1-Week-3/Course-1-Week-3-Practice-Labs/public_tests.py
  function sigmoid_test (line 4) | def sigmoid_test(target):
  function compute_cost_test (line 11) | def compute_cost_test(target):
  function compute_gradient_test (line 45) | def compute_gradient_test(target):
  function predict_test (line 59) | def predict_test(target):
  function compute_cost_reg_test (line 84) | def compute_cost_reg_test(target):
  function compute_gradient_reg_test (line 114) | def compute_gradient_reg_test(target):

FILE: Course-1-Supervised-Machine-Learning-Regression-and-Classification/Course-1-Week-3/Course-1-Week-3-Practice-Labs/test_utils.py
  function datatype_check (line 5) | def datatype_check(expected_output, target_output, error):
  function equation_output_check (line 44) | def equation_output_check(expected_output, target_output, error):
  function shape_check (line 79) | def shape_check(expected_output, target_output, error):
  function single_test (line 110) | def single_test(test_cases, target):
  function multiple_test (line 138) | def multiple_test(test_cases, target):

FILE: Course-1-Supervised-Machine-Learning-Regression-and-Classification/Course-1-Week-3/Course-1-Week-3-Practice-Labs/utils.py
  function load_data (line 4) | def load_data(filename):
  function sig (line 10) | def sig(z):
  function map_feature (line 14) | def map_feature(X1, X2):
  function plot_data (line 28) | def plot_data(X, y, pos_label="y=1", neg_label="y=0"):
  function plot_decision_boundary (line 37) | def plot_decision_boundary(w, b, X, y):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-1/Course-2-Week-1-Optional-Labs/lab_coffee_utils.py
  function load_coffee_data (line 10) | def load_coffee_data():
  function plt_roast (line 32) | def plt_roast(X,Y):
  function plt_prob (line 49) | def plt_prob(ax,fwb):
  function truncate_colormap (line 71) | def truncate_colormap(cmap, minval=0.0, maxval=1.0, n=100):
  function plt_layer (line 78) | def plt_layer(X,Y,W1,b1,norm_l):
  function plt_network (line 96) | def plt_network(X,Y,netf):
  function plt_output_unit (line 125) | def plt_output_unit(W,b):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-1/Course-2-Week-1-Optional-Labs/lab_neurons_utils.py
  function plt_prob_1d (line 8) | def plt_prob_1d(ax,fwb):
  function truncate_colormap (line 27) | def truncate_colormap(cmap, minval=0.0, maxval=1.0, n=100):
  function sigmoidnp (line 35) | def sigmoidnp(z):
  function plt_linear (line 54) | def plt_linear(X_train, Y_train, prediction_tf, prediction_np):
  function plt_logistic (line 74) | def plt_logistic(X_train, Y_train, model, set_w, set_b, pos, neg):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-1/Course-2-Week-1-Optional-Labs/lab_utils_common.py
  function sigmoid (line 24) | def sigmoid(z):
  function predict_logistic (line 47) | def predict_logistic(X, w, b):
  function predict_linear (line 51) | def predict_linear(X, w, b):
  function compute_cost_logistic (line 55) | def compute_cost_logistic(X, y, w, b, lambda_=0, safe=False):
  function log_1pexp (line 90) | def log_1pexp(x, maximum=20):
  function compute_cost_matrix (line 107) | def compute_cost_matrix(X, y, w, b, logistic=False, lambda_=0, safe=True):
  function compute_gradient_matrix (line 141) | def compute_gradient_matrix(X, y, w, b, logistic=False, lambda_=0):
  function gradient_descent (line 169) | def gradient_descent(X, y, w_in, b_in, alpha, num_iters, logistic=False,...
  function zscore_normalize_features (line 222) | def zscore_normalize_features(X):
  function plot_data (line 252) | def plot_data(X, y, ax, pos_label="y=1", neg_label="y=0", s=80, loc='bes...
  function plt_tumor_data (line 269) | def plt_tumor_data(x, y, ax):
  function draw_vthresh (line 286) | def draw_vthresh(ax,x):
  class button_manager (line 312) | class button_manager:
    method __init__ (line 322) | def __init__(self,fig, dim, labels, init, call_on_click):
    method reinit (line 338) | def reinit(self):
    method button_click (line 343) | def button_click(self, event):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-1/Course-2-Week-1-Optional-Labs/public_tests.py
  function test_c1 (line 7) | def test_c1(target):
  function test_c2 (line 28) | def test_c2(target):
  function test_c3 (line 57) | def test_c3(target):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-1/Course-2-Week-1-Optional-Labs/utils.py
  function sigmoid (line 6) | def sigmoid(x):
  function plot_mc_data (line 10) | def plot_mc_data(X, y, class_labels=None, legend=False,size=40):
  function plot_cat_decision_boundary (line 22) | def plot_cat_decision_boundary(X,predict , class_labels=None, legend=Fal...

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-1/Course-2-Week-1-Practice-Labs/autils.py
  function load_data (line 3) | def load_data():
  function load_weights (line 10) | def load_weights():
  function sigmoid (line 17) | def sigmoid(x):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-1/Course-2-Week-1-Practice-Labs/lab_neurons_utils.py
  function plt_prob_1d (line 8) | def plt_prob_1d(ax,fwb):
  function truncate_colormap (line 27) | def truncate_colormap(cmap, minval=0.0, maxval=1.0, n=100):
  function sigmoidnp (line 35) | def sigmoidnp(z):
  function plt_linear (line 54) | def plt_linear(X_train, Y_train, prediction_tf, prediction_np):
  function plt_logistic (line 74) | def plt_logistic(X_train, Y_train, model, set_w, set_b, pos, neg):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-1/Course-2-Week-1-Practice-Labs/lab_utils_common.py
  function sigmoid (line 24) | def sigmoid(z):
  function predict_logistic (line 47) | def predict_logistic(X, w, b):
  function predict_linear (line 51) | def predict_linear(X, w, b):
  function compute_cost_logistic (line 55) | def compute_cost_logistic(X, y, w, b, lambda_=0, safe=False):
  function log_1pexp (line 90) | def log_1pexp(x, maximum=20):
  function compute_cost_matrix (line 107) | def compute_cost_matrix(X, y, w, b, logistic=False, lambda_=0, safe=True):
  function compute_gradient_matrix (line 141) | def compute_gradient_matrix(X, y, w, b, logistic=False, lambda_=0):
  function gradient_descent (line 169) | def gradient_descent(X, y, w_in, b_in, alpha, num_iters, logistic=False,...
  function zscore_normalize_features (line 222) | def zscore_normalize_features(X):
  function plot_data (line 252) | def plot_data(X, y, ax, pos_label="y=1", neg_label="y=0", s=80, loc='bes...
  function plt_tumor_data (line 269) | def plt_tumor_data(x, y, ax):
  function draw_vthresh (line 286) | def draw_vthresh(ax,x):
  class button_manager (line 312) | class button_manager:
    method __init__ (line 322) | def __init__(self,fig, dim, labels, init, call_on_click):
    method reinit (line 338) | def reinit(self):
    method button_click (line 343) | def button_click(self, event):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-1/Course-2-Week-1-Practice-Labs/public_tests.py
  function test_c1 (line 7) | def test_c1(target):
  function test_c2 (line 28) | def test_c2(target):
  function test_c3 (line 57) | def test_c3(target):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-1/Course-2-Week-1-Practice-Labs/utils.py
  function sigmoid (line 6) | def sigmoid(x):
  function plot_mc_data (line 10) | def plot_mc_data(X, y, class_labels=None, legend=False,size=40):
  function plot_cat_decision_boundary (line 22) | def plot_cat_decision_boundary(X,predict , class_labels=None, legend=Fal...

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-2/Course-2-Week-2-Optional-Labs/autils.py
  function load_data (line 14) | def load_data():
  function plt_act_trio (line 19) | def plt_act_trio():
  function widgvis (line 39) | def widgvis(fig):
  function plt_ex1 (line 44) | def plt_ex1():
  function plt_ex2 (line 58) | def plt_ex2():
  function gen_data (line 72) | def gen_data():
  function plt_dual (line 78) | def plt_dual(X,y,yhat):
  function plt_act1 (line 93) | def plt_act1(X,y,z,a):
  function plt_add_notation (line 117) | def plt_add_notation(ax):
  function compile_fit (line 128) | def compile_fit(model,X,y):
  function plt_model (line 145) | def plt_model(X,y,yhat_pre, yhat_post):
  function display_errors (line 165) | def display_errors(model,X,y):
  function display_digit (line 196) | def display_digit(X):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-2/Course-2-Week-2-Optional-Labs/lab_utils_common.py
  function sigmoid (line 24) | def sigmoid(z):
  function predict_logistic (line 47) | def predict_logistic(X, w, b):
  function predict_linear (line 51) | def predict_linear(X, w, b):
  function compute_cost_logistic (line 55) | def compute_cost_logistic(X, y, w, b, lambda_=0, safe=False):
  function log_1pexp (line 90) | def log_1pexp(x, maximum=20):
  function compute_cost_matrix (line 107) | def compute_cost_matrix(X, y, w, b, logistic=False, lambda_=0, safe=True):
  function compute_gradient_matrix (line 141) | def compute_gradient_matrix(X, y, w, b, logistic=False, lambda_=0):
  function gradient_descent (line 169) | def gradient_descent(X, y, w_in, b_in, alpha, num_iters, logistic=False,...
  function zscore_normalize_features (line 222) | def zscore_normalize_features(X):
  function plot_data (line 252) | def plot_data(X, y, ax, pos_label="y=1", neg_label="y=0", s=80, loc='bes...
  function plt_tumor_data (line 269) | def plt_tumor_data(x, y, ax):
  function draw_vthresh (line 286) | def draw_vthresh(ax,x):
  class button_manager (line 312) | class button_manager:
    method __init__ (line 322) | def __init__(self,fig, dim, labels, init, call_on_click):
    method reinit (line 338) | def reinit(self):
    method button_click (line 343) | def button_click(self, event):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-2/Course-2-Week-2-Optional-Labs/lab_utils_multiclass.py
  function sigmoid (line 6) | def sigmoid(x):
  function plot_mc_data (line 10) | def plot_mc_data(X, y, class_labels=None, legend=False,size=40):
  function plot_cat_decision_boundary (line 22) | def plot_cat_decision_boundary(X,predict , class_labels=None, legend=Fal...

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-2/Course-2-Week-2-Optional-Labs/lab_utils_multiclass_TF.py
  function plot_cat_decision_boundary_mc (line 26) | def plot_cat_decision_boundary_mc(ax, X, predict , class_labels=None, le...
  function plt_mc_data (line 52) | def plt_mc_data(ax, X, y, classes,  class_labels=None, map=plt.cm.Paired,
  function plt_mc (line 69) | def plt_mc(X_train,y_train,classes, centers, std):
  function plt_cat_mc (line 84) | def plt_cat_mc(X_train, y_train, model, classes):
  function plt_prob_z (line 104) | def plt_prob_z(ax,fwb, x0_rng=(-8,8), x1_rng=(-5,4)):
  function truncate_colormap (line 134) | def truncate_colormap(cmap, minval=0.0, maxval=1.0, n=100):
  function plt_layer_relu (line 142) | def plt_layer_relu(X, Y, W1, b1, classes):
  function plt_output_layer_linear (line 161) | def plt_output_layer_linear(X, Y, W, b, classes, x0_rng=None, x1_rng=None):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-2/Course-2-Week-2-Optional-Labs/lab_utils_relu.py
  function widgvis (line 8) | def widgvis(fig):
  function plt_base (line 14) | def plt_base(ax):
  function plt_yhat (line 31) | def plt_yhat(ax, X, w00, b00, w01, b01, w02, b02):
  function plt_unit (line 38) | def plt_unit(ax, X, w, b):
  function plt_relu_ex (line 50) | def plt_relu_ex():

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-2/Course-2-Week-2-Optional-Labs/lab_utils_softmax.py
  function plt_softmax (line 10) | def plt_softmax(my_softmax):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-2/Course-2-Week-2-Practice-Labs/autils.py
  function load_data (line 14) | def load_data():
  function plt_act_trio (line 19) | def plt_act_trio():
  function widgvis (line 39) | def widgvis(fig):
  function plt_ex1 (line 44) | def plt_ex1():
  function plt_ex2 (line 58) | def plt_ex2():
  function gen_data (line 72) | def gen_data():
  function plt_dual (line 78) | def plt_dual(X,y,yhat):
  function plt_act1 (line 93) | def plt_act1(X,y,z,a):
  function plt_add_notation (line 117) | def plt_add_notation(ax):
  function compile_fit (line 128) | def compile_fit(model,X,y):
  function plt_model (line 145) | def plt_model(X,y,yhat_pre, yhat_post):
  function display_errors (line 165) | def display_errors(model,X,y):
  function display_digit (line 196) | def display_digit(X):
  function plot_loss_tf (line 206) | def plot_loss_tf(history):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-2/Course-2-Week-2-Practice-Labs/lab_utils_common.py
  function sigmoid (line 24) | def sigmoid(z):
  function predict_logistic (line 47) | def predict_logistic(X, w, b):
  function predict_linear (line 51) | def predict_linear(X, w, b):
  function compute_cost_logistic (line 55) | def compute_cost_logistic(X, y, w, b, lambda_=0, safe=False):
  function log_1pexp (line 90) | def log_1pexp(x, maximum=20):
  function compute_cost_matrix (line 107) | def compute_cost_matrix(X, y, w, b, logistic=False, lambda_=0, safe=True):
  function compute_gradient_matrix (line 141) | def compute_gradient_matrix(X, y, w, b, logistic=False, lambda_=0):
  function gradient_descent (line 169) | def gradient_descent(X, y, w_in, b_in, alpha, num_iters, logistic=False,...
  function zscore_normalize_features (line 222) | def zscore_normalize_features(X):
  function plot_data (line 252) | def plot_data(X, y, ax, pos_label="y=1", neg_label="y=0", s=80, loc='bes...
  function plt_tumor_data (line 269) | def plt_tumor_data(x, y, ax):
  function draw_vthresh (line 286) | def draw_vthresh(ax,x):
  class button_manager (line 312) | class button_manager:
    method __init__ (line 322) | def __init__(self,fig, dim, labels, init, call_on_click):
    method reinit (line 338) | def reinit(self):
    method button_click (line 343) | def button_click(self, event):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-2/Course-2-Week-2-Practice-Labs/lab_utils_softmax.py
  function plt_softmax (line 10) | def plt_softmax(my_softmax):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-2/Course-2-Week-2-Practice-Labs/public_tests.py
  function test_my_softmax (line 7) | def test_my_softmax(target):
  function test_model (line 22) | def test_model(target, classes, input_size):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-3/Course-2-Week-3-Practice-Labs/assigment_utils.py
  function gen_data (line 28) | def gen_data(m, seed=1, scale=0.7):
  function gen_blobs (line 38) | def gen_blobs():
  class lin_model (line 46) | class lin_model:
    method __init__ (line 47) | def __init__(self, degree, regularization = False, lambda_=0):
    method fit (line 55) | def fit(self, X_train,y_train):
    method predict (line 61) | def predict(self, X):
    method mse (line 67) | def mse(self, y, yhat):
  function plt_train_test (line 71) | def plt_train_test(X_train, y_train, X_test, y_test, x, y_pred, x_ideal,...
  function plt_optimal_degree (line 91) | def plt_optimal_degree(X_train, y_train, X_cv, y_cv, x, y_pred, x_ideal,...
  function plt_tune_regularization (line 128) | def plt_tune_regularization(X_train, y_train, X_cv, y_cv, x, y_pred, err...
  function tune_m (line 165) | def tune_m():
  function plt_tune_m (line 190) | def plt_tune_m(X_train, y_train, X_cv, y_cv, x, y_pred, err_train, err_c...
  function plt_mc_data (line 227) | def plt_mc_data(ax, X, y, classes,  class_labels=None, map=plt.cm.Paired...
  function plot_cat_decision_boundary (line 241) | def plot_cat_decision_boundary(ax, X,predict , class_labels=None, legend...
  function recat (line 265) | def recat(pt, origins):
  function plt_train_eq_dist (line 279) | def plt_train_eq_dist(X_train,y_train,classes, X_cv,   y_cv, centers, std):
  function plt_nn (line 304) | def plt_nn(model_predict,X_train,y_train, classes, X_cv, y_cv, suptitle=...
  function eval_cat_err (line 326) | def eval_cat_err(y, yhat):
  function plot_iterate (line 343) | def plot_iterate(lambdas, models, X_train, y_train, X_cv, y_cv):
  function err_all_equal (line 368) | def err_all_equal(X_train,X_cv,X_test, y_train,y_cv,y_test, centers):
  function plt_compare (line 378) | def plt_compare(X,y, classes, simple, regularized, centers):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-3/Course-2-Week-3-Practice-Labs/public_tests_a1.py
  function test_eval_mse (line 10) | def test_eval_mse(target):
  function test_eval_cat_err (line 34) | def test_eval_cat_err(target):
  function model_test (line 57) | def model_test(target, classes, input_size):
  function model_s_test (line 88) | def model_s_test(target, classes, input_size):
  function model_r_test (line 118) | def model_r_test(target, classes, input_size):

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-3/Course-2-Week-3-Practice-Labs/utils.py
  function load_data (line 5) | def load_data():

FILE: Course-2-Advanced-Learning-Algorithms/Course-2-Week-4/Course-2-Week-4-Practice-Labs/public_tests.py
  function compute_entropy_test (line 3) | def compute_entropy_test(target):
  function split_dataset_test (line 25) | def split_dataset_test(target):
  function compute_information_gain_test (line 77) | def compute_information_gain_test(target):
  function get_best_split_test (line 110) | def get_best_split_test(target):

FILE: Course-3-Unsupervised-Learning-Recommenders-Reinforcement-Learning/Course-3-Week-1/Course-3-Week-1-Practice-Labs/public_tests.py
  function compute_centroids_test (line 3) | def compute_centroids_test(target):
  function find_closest_centroids_test (line 32) | def find_closest_centroids_test(target):

FILE: Course-3-Unsupervised-Learning-Recommenders-Reinforcement-Learning/Course-3-Week-1/Course-3-Week-1-Practice-Labs/utils.py
  function load_data (line 4) | def load_data():
  function draw_line (line 8) | def draw_line(p1, p2, style="-k", linewidth=1):
  function plot_data_points (line 11) | def plot_data_points(X, idx):
  function plot_progress_kMeans (line 16) | def plot_progress_kMeans(X, centroids, previous_centroids, idx, K, i):

FILE: Course-3-Unsupervised-Learning-Recommenders-Reinforcement-Learning/Course-3-Week-2/Course-3-Week-2-Practice-Labs/public_tests.py
  function test_tower (line 6) | def test_tower(target):
  function test_sq_dist (line 26) | def test_sq_dist(target):

FILE: Course-3-Unsupervised-Learning-Recommenders-Reinforcement-Learning/Course-3-Week-2/Course-3-Week-2-Practice-Labs/recsysNN_utils.py
  function load_data (line 15) | def load_data():
  function pprint_train (line 46) | def pprint_train(x_train, features,  vs, u_s, maxcount = 5, user=True):
  function pprint_data (line 76) | def pprint_data(y_p, user_train, item_train, printfull=False):
  function split_str (line 101) | def split_str(ifeatures, smax):
  function pprint_data_tab (line 111) | def pprint_data_tab(y_p, user_train, item_train, uvs, ivs, user_features...
  function print_pred_movies (line 142) | def print_pred_movies(y_p, user, item, movie_dict, maxcount=10):
  function gen_user_vecs (line 163) | def gen_user_vecs(user_vec, num_items):
  function predict_uservec (line 170) | def predict_uservec(user_vecs, item_vecs, model, u_s, i_s, scaler, Scale...
  function print_pred_debug (line 192) | def print_pred_debug(y_p, y, user, item, maxcount=10, onlyrating=False, ...
  function get_user_vecs (line 221) | def get_user_vecs(user_id, user_train, item_vecs, user_to_genre):
  function get_item_genre (line 252) | def get_item_genre(item, ivs, item_features):
  function print_existing_user (line 258) | def print_existing_user(y_p, y, user, items, item_features, ivs, uvs, mo...

FILE: Course-3-Unsupervised-Learning-Recommenders-Reinforcement-Learning/Course-3-Week-2/Course-3-Week-2-Practice-Labs/recsys_utils.py
  function normalizeRatings (line 5) | def normalizeRatings(Y, R):
  function load_precalc_params_small (line 17) | def load_precalc_params_small():
  function load_ratings_small (line 32) | def load_ratings_small():
  function load_Movie_List_pd (line 40) | def load_Movie_List_pd():

FILE: Course-3-Unsupervised-Learning-Recommenders-Reinforcement-Learning/Course-3-Week-3/Course-3-Week-3-Optional-Labs/utils.py
  function generate_rewards (line 4) | def generate_rewards(num_states, each_step_reward, terminal_left_reward,...
  function generate_transition_prob (line 12) | def generate_transition_prob(num_states, num_actions, misstep_prob = 0):
  function calculate_Q_value (line 32) | def calculate_Q_value(num_states, rewards, transition_prob, gamma, V_sta...
  function evaluate_policy (line 36) | def evaluate_policy(num_states, rewards, transition_prob, gamma, policy):
  function improve_policy (line 54) | def improve_policy(num_states, num_actions, rewards, transition_prob, ga...
  function get_optimal_policy (line 69) | def get_optimal_policy(num_states, num_actions, rewards, transition_prob...
  function calculate_Q_values (line 84) | def calculate_Q_values(num_states, rewards, transition_prob, gamma, opti...
  function plot_optimal_policy_return (line 100) | def plot_optimal_policy_return(num_states, optimal_policy, rewards, V):
  function plot_q_values (line 120) | def plot_q_values(num_states, q_left_star, q_right_star, rewards):
  function generate_visualization (line 137) | def generate_visualization(terminal_left_reward, terminal_right_reward, ...

FILE: Course-3-Unsupervised-Learning-Recommenders-Reinforcement-Learning/Course-3-Week-3/Course-3-Week-3-Practice-Labs/public_tests.py
  function test_network (line 7) | def test_network(target):
  function test_optimizer (line 29) | def test_optimizer(target, ALPHA):
  function test_compute_loss (line 35) | def test_compute_loss(target):

FILE: Course-3-Unsupervised-Learning-Recommenders-Reinforcement-Learning/Course-3-Week-3/Course-3-Week-3-Practice-Labs/utils.py
  function get_experiences (line 25) | def get_experiences(memory_buffer):
  function check_update_conditions (line 36) | def check_update_conditions(t, num_steps_upd, memory_buffer):
  function get_new_eps (line 43) | def get_new_eps(epsilon):
  function get_action (line 47) | def get_action(q_values, epsilon=0):
  function update_target_network (line 54) | def update_target_network(q_network, target_q_network):
  function plot_history (line 59) | def plot_history(reward_history, rolling_window=20, lower_limit=None,
  function display_table (line 94) | def display_table(initial_state, action, next_state, reward, done):
  function embed_mp4 (line 115) | def embed_mp4(filename):
  function create_video (line 127) | def create_video(filename, env, q_network, fps=30):