1 - Promo Highlights (285.91 MB)
10 - Basics of Deep Learning N Dimensional Space (10.32 MB)
11 - Basics of Deep Learning Theory of Perceptron (4.4 MB)
12 - Basics of Deep Learning Implementing Basic Perceptron (17.54 MB)
13 - Basics of Deep Learning Logical Gates for Perceptrons (8.07 MB)
14 - Basics of Deep Learning Perceptron Training Part 1 (3.18 MB)
15 - Basics of Deep Learning Perceptron Training Part 2 (12.94 MB)
16 - Basics of Deep Learning Learning Rate (11.83 MB)
17 - Basics of Deep Learning Perceptron Training Part 3 (13.82 MB)
18 - Basics of Deep Learning Perceptron Algorithm (3.17 MB)
19 - Basics of Deep Learning Coading Perceptron Algo Data Reading Visualization (34.37 MB)
2 - Introduction Introduction to Instructor and Aisciences (79.34 MB)
20 - Basics of Deep Learning Coading Perceptron Algo Perceptron Step (47.16 MB)
21 - Basics of Deep Learning Coading Perceptron Algo Training Perceptron (42.19 MB)
22 - Basics of Deep Learning Coading Perceptron Algo Visualizing the Results (19.78 MB)
23 - Basics of Deep Learning Problem with Linear Solutions (9.44 MB)
24 - Basics of Deep Learning Solution to Problem (4.24 MB)
25 - Basics of Deep Learning Error Functions (6.32 MB)
26 - Basics of Deep Learning Discrete vs Continuous Error Function (8.97 MB)
27 - Basics of Deep Learning Sigmoid Function (9.34 MB)
28 - Basics of Deep Learning MultiClass Problem (5.57 MB)
29 - Basics of Deep Learning Problem of Negative Scores (10.12 MB)
30 - Basics of Deep Learning Need of Softmax (4.57 MB)
31 - Basics of Deep Learning Coding Softmax (16.63 MB)
32 - Basics of Deep Learning One Hot Encoding (6.84 MB)
33 - Basics of Deep Learning Maximum Likelihood Part 1 (15.32 MB)
34 - Basics of Deep Learning Maximum Likelihood Part 2 (12.16 MB)
35 - Basics of Deep Learning Cross Entropy (11.24 MB)
36 - Basics of Deep Learning Cross Entropy Formulation (33.67 MB)
37 - Basics of Deep Learning Multi Class Cross Entropy (27.62 MB)
38 - Basics of Deep Learning Cross Entropy Implementation (16.47 MB)
39 - Basics of Deep Learning Sigmoid Function Implementation (3.64 MB)
4 - Basics of Deep Learning Problem to Solve Part 1 (8.05 MB)
40 - Basics of Deep Learning Output Function Implementation (9.9 MB)
41 - Deep Learning Introduction to Gradient Decent (29.39 MB)
42 - Deep Learning Convex Functions (8.6 MB)
43 - Deep Learning Use of Derivatives (10.32 MB)
44 - Deep Learning How Gradient Decent Works (8.36 MB)
45 - Deep Learning Gradient Step (6.22 MB)
46 - Deep Learning Logistic Regression Algorithm (4.87 MB)
47 - Deep Learning Data Visualization and Reading (51.78 MB)
48 - Deep Learning Updating Weights in Python (18.59 MB)
49 - Deep Learning Implementing Logistic Regression (75.47 MB)
5 - Basics of Deep Learning Problem to Solve Part 2 (7.58 MB)
50 - Deep Learning Visualization and Results (60.13 MB)
51 - Deep Learning Gradient Decent vs Perceptron (18.57 MB)
52 - Deep Learning Linear to Non Linear Boundaries (17.59 MB)
53 - Deep Learning Combining Probabilities (8.75 MB)
54 - Deep Learning Weighted Sums (12.48 MB)
55 - Deep Learning Neural Network Architecture (56.86 MB)
56 - Deep Learning Layers and DEEP Networks (21.19 MB)
57 - Deep Learning Multi Class Classification (14.22 MB)
58 - Deep Learning Basics of Feed Forward (28.52 MB)
59 - Deep Learning Feed Forward for DEEP Net (24.38 MB)
6 - Basics of Deep Learning Problem to Solve Part 3 (6.04 MB)
60 - Deep Learning Deep Learning Algo Overview (8.04 MB)
61 - Deep Learning Basics of Back Propagation (24.79 MB)
62 - Deep Learning Updating Weights (12.75 MB)
63 - Deep Learning Chain Rule for BackPropagation (21.39 MB)
64 - Deep Learning Sigma Prime (6.91 MB)
65 - Deep Learning Data Analysis NN Implementation (44.31 MB)
66 - Deep Learning One Hot Encoding NN Implementation (21.25 MB)
67 - Deep Learning Scaling the Data NN Implementation (6.34 MB)
68 - Deep Learning Splitting the Data NN Implementation (18.71 MB)
69 - Deep Learning Helper Functions NN Implementation (8.87 MB)
7 - Basics of Deep Learning Linear Equation (11.54 MB)
70 - Deep Learning Training NN Implementation (70.51 MB)
71 - Deep Learning Testing NN Implementation (23.09 MB)
72 - Optimizations Underfitting vs Overfitting (27.39 MB)
73 - Optimizations Early Stopping (12.34 MB)
74 - Optimizations Quiz (1.67 MB)
75 - Optimizations Solution Regularization (18.04 MB)
76 - Optimizations L1 L2 Regularization (8.99 MB)
77 - Optimizations Dropout (11 MB)
78 - Optimizations Local Minima Problem (7.4 MB)
79 - Optimizations Random Restart Solution (12.91 MB)
8 - Basics of Deep Learning Linear Equation Vectorized (11.27 MB)
80 - Optimizations Vanishing Gradient Problem (12.47 MB)
81 - Optimizations Other Activation Functions (18.42 MB)
82 - Final Project Final Project Part 1 (94.72 MB)
83 - Final Project Final Project Part 2 (119.12 MB)
84 - Final Project Final Project Part 3 (82.28 MB)
85 - Final Project Final Project Part 4 (48.99 MB)
86 - Final Project Final Project Part 5 (79.67 MB)
9 - Basics of Deep Learning 3D Feature Space (17.48 MB)
100 - NN with Tensor Basic NN part 1 (57.75 MB)
101 - NN with Tensor Basic NN part 2 (90.1 MB)
102 - NN with Tensor Loss Functions (119.64 MB)
103 - NN with Tensor Activation Functions Hidden Layers (91.95 MB)
104 - NN with Tensor Optimizers (116.89 MB)
105 - NN with Tensor Data Loader Dataset (43.13 MB)
106 - NN with Tensor Activity (75.82 MB)
107 - NN with Tensor Activity Solution (139.03 MB)
108 - NN with Tensor Formating the Output (24.84 MB)
109 - NN with Tensor Graph for Loss (30.36 MB)
110 - CNN Introduction to Module (78.65 MB)
111 - CNN CNN vs NN (70.68 MB)
112 - CNN Introduction to Convolution (19.65 MB)
113 - CNN Convolution Animations (90.02 MB)
114 - CNN Convolution using Pytorch (56.95 MB)
115 - CNN Introduction to Pooling (9.87 MB)
116 - CNN Pooling using Numpy (27.05 MB)
117 - CNN Pooling in Pytorch (114.41 MB)
118 - CNN Introduction to Project (109.73 MB)
119 - CNN Project Data Loading (70.75 MB)
120 - CNN Project Transforms (88.33 MB)
121 - CNN Project DataLoaders (47.5 MB)
122 - CNN Project CNN Architect (60.57 MB)
123 - CNN Project Forward Propagation (93.76 MB)
124 - CNN Project Training CNN (171.91 MB)
125 - CNN Project Analyzing Model Output (46.64 MB)
126 - CNN Project Making Predictions (24.4 MB)
88 - Introduction Module Content (207.48 MB)
89 - Introduction Benefits of Framework (121.86 MB)
90 - Introduction Installations and Setups (78.46 MB)
91 - Tensor Introduction to Tensor (55.08 MB)
92 - Tensor List vs Array vs Tensor (40.14 MB)
93 - Tensor Arithmetic Operations (45.95 MB)
94 - Tensor Tensor Operations (44.41 MB)
95 - Tensor AutoGradiants (83.22 MB)
96 - Tensor Activity Solution (13.01 MB)
97 - Tensor Detaching Gradients (51.55 MB)
98 - Tensor Loading GPU (58.85 MB)
99 - NN with Tensor Introduction to Module (59.94 MB)
128 - Introduction to TensorFlow Module Introduction (74.26 MB)
129 - Introduction to TensorFlow TensorFlow Definition and Properties (12.44 MB)
130 - Introduction to TensorFlow Tensor Types and Tesnor Board (11.5 MB)
131 - Introduction to TensorFlow How to use TensorFlow (7.86 MB)
132 - Introduction to TensorFlow Google Colab (5.09 MB)
133 - Introduction to TensorFlow Exercise (10.46 MB)
134 - Introduction to TensorFlow Exercise Solution (68.88 MB)
135 - Introduction to TensorFlow Quiz (7.53 MB)
136 - Introduction to TensorFlow Quiz Solution (123.79 MB)
137 - Building your first deep learning Project Module Introduction (82.86 MB)
138 - Building your first deep learning Project ANNs (20.98 MB)
139 - Building your first deep learning Project TensorFlow Playground (19.82 MB)
140 - Building your first deep learning Project Load TF and Data (6.62 MB)
141 - Building your first deep learning Project Model Training and Evaluation (10.76 MB)
142 - Building your first deep learning Project Project (9.38 MB)
143 - Building your first deep learning Project Project Implementation (136.12 MB)
144 - Building your first deep learning Project Quiz (3.49 MB)
145 - Building your first deep learning Project Quiz Solution (54.86 MB)
146 - Multilayer Deep Learning Project Module Introduction (155.42 MB)
147 - Multilayer Deep Learning Project Training and Epochs (18.95 MB)
148 - Multilayer Deep Learning Project Gradient Decent and Back Propagation (20.71 MB)
149 - Multilayer Deep Learning Project Bias Variance TradeOff (12.41 MB)
150 - Multilayer Deep Learning Project Performance Metrics (48.9 MB)
151 - Multilayer Deep Learning Project ProjectSales Predition (144.56 MB)
152 - Multilayer Deep Learning Project Quiz (5.51 MB)
153 - Multilayer Deep Learning Project Quiz Solution (72.44 MB)