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| [TGx]Downloaded from torrentgalaxy.to .txt |
585B |
| 1. Class Imbalance - Why Is Accuracy Not Always The Best Metric .mp4 |
44.30MB |
| 1. Class Imbalance - Why Is Accuracy Not Always The Best Metric .srt |
9.52KB |
| 1. Derivation Of Back Propagation - Part 1.mp4 |
51.12MB |
| 1. Derivation Of Back Propagation - Part 1.srt |
7.98KB |
| 1. Get My Other Courses !.html |
1.88KB |
| 1. Gradient Descent With Momentum - Part 1.mp4 |
45.78MB |
| 1. Gradient Descent With Momentum - Part 1.srt |
11.93KB |
| 1. Introduction To Batch Normalization - Part 1.mp4 |
61.82MB |
| 1. Introduction To Batch Normalization - Part 1.srt |
15.08KB |
| 1. Introduction To Multi-Layer Perceptrons.mp4 |
97.61MB |
| 1. Introduction To Multi-Layer Perceptrons.srt |
18.29KB |
| 1. Introduction To The Classification Problem.mp4 |
38.31MB |
| 1. Introduction To The Classification Problem.srt |
8.56KB |
| 1. Promo Video.mp4 |
33.92MB |
| 1. Promo Video.srt |
1.99KB |
| 1. Regression, Overfitting, And Underfitting.mp4 |
76.96MB |
| 1. Regression, Overfitting, And Underfitting.srt |
21.92KB |
| 1. Source Of Those Lectures.html |
256B |
| 1. The Error Function.mp4 |
61.42MB |
| 1. The Error Function.srt |
11.92KB |
| 1. The Perceptron Learning Rule - Part 1.mp4 |
22.47MB |
| 1. The Perceptron Learning Rule - Part 1.srt |
6.69KB |
| 1. The Sigmoid And Bernoulli Distribution.mp4 |
45.10MB |
| 1. The Sigmoid And Bernoulli Distribution.srt |
7.93KB |
| 10. Changing Activation Functions - Tanh - Relu - LeakyRelu.mp4 |
83.41MB |
| 10. Changing Activation Functions - Tanh - Relu - LeakyRelu.srt |
18.78KB |
| 10. Types Of Machine Learning.mp4 |
54.94MB |
| 10. Types Of Machine Learning.srt |
11.91KB |
| 11. Solved Example (I) Single Layer Perceptron Designed Graphically.mp4 |
84.11MB |
| 11. Solved Example (I) Single Layer Perceptron Designed Graphically.srt |
15.22KB |
| 2.1 WrittenNotes.rar |
13.15MB |
| 2. A Simple Glimpse Of Overfitting.mp4 |
26.15MB |
| 2. A Simple Glimpse Of Overfitting.srt |
5.88KB |
| 2. Derivation Of Back Propagation - Part 2.mp4 |
117.32MB |
| 2. Derivation Of Back Propagation - Part 2.srt |
14.68KB |
| 2. Gradient Descent With Momentum - Part 2.mp4 |
59.47MB |
| 2. Gradient Descent With Momentum - Part 2.srt |
15.97KB |
| 2. Introduction To Batch Normalization - Part 2.mp4 |
36.34MB |
| 2. Introduction To Batch Normalization - Part 2.srt |
8.01KB |
| 2. Introduction To Machine Learning.mp4 |
36.62MB |
| 2. Introduction To Machine Learning.srt |
10.90KB |
| 2. Introduction To Reglarization.mp4 |
69.84MB |
| 2. Introduction To Reglarization.srt |
12.04KB |
| 2. Maximum Likelihood Estimation - Quick Overview.mp4 |
47.21MB |
| 2. Maximum Likelihood Estimation - Quick Overview.srt |
12.94KB |
| 2. Precision - Recall , And F1 Score.mp4 |
38.81MB |
| 2. Precision - Recall , And F1 Score.srt |
7.65KB |
| 2. Solved Example (II) MLP Design Graphically.mp4 |
111.76MB |
| 2. Solved Example (II) MLP Design Graphically.srt |
16.54KB |
| 2. The Cross Entropy Cost Function - Derivation.mp4 |
73.42MB |
| 2. The Cross Entropy Cost Function - Derivation.srt |
16.39KB |
| 2. The Perceptron Learning Rule - Part 2.mp4 |
53.44MB |
| 2. The Perceptron Learning Rule - Part 2.srt |
13.14KB |
| 2. The Sigmoid Activation Function Again.mp4 |
53.77MB |
| 2. The Sigmoid Activation Function Again.srt |
10.42KB |
| 3. Adagrad And RMSProb.mp4 |
61.16MB |
| 3. Adagrad And RMSProb.srt |
14.44KB |
| 3. Derivation Of Back Propagation - Part 3.mp4 |
127.44MB |
| 3. Derivation Of Back Propagation - Part 3.srt |
16.91KB |
| 3. Deriving The Gradient Descent Algorithm.mp4 |
47.76MB |
| 3. Deriving The Gradient Descent Algorithm.srt |
11.15KB |
| 3. Different Ways For Regularization.mp4 |
35.73MB |
| 3. Different Ways For Regularization.srt |
6.50KB |
| 3. F1 Score vs Simple Average.mp4 |
26.62MB |
| 3. F1 Score vs Simple Average.srt |
7.02KB |
| 3. Forward Pass Equations For Batch Normalization.mp4 |
55.84MB |
| 3. Forward Pass Equations For Batch Normalization.srt |
14.00KB |
| 3. Intuition Of Multi-Layer Perceptrons - Part 1.mp4 |
69.82MB |
| 3. Intuition Of Multi-Layer Perceptrons - Part 1.srt |
13.88KB |
| 3. Maximum Likelihood Estimation Of Gaussian Distribution Parameters.mp4 |
60.00MB |
| 3. Maximum Likelihood Estimation Of Gaussian Distribution Parameters.srt |
10.53KB |
| 3. Proof Perceptron Convergence Theorem - Part 1.mp4 |
101.96MB |
| 3. Proof Perceptron Convergence Theorem - Part 1.srt |
17.80KB |
| 3. The Cross Entropy & The Vanishing Gradient Problem.mp4 |
45.63MB |
| 3. The Cross Entropy & The Vanishing Gradient Problem.srt |
9.78KB |
| 3. The Perceptron Equation.mp4 |
42.41MB |
| 3. The Perceptron Equation.srt |
9.40KB |
| 4. Adam And Learning Rate Decay.mp4 |
65.60MB |
| 4. Adam And Learning Rate Decay.srt |
15.14KB |
| 4. Batch Normalization Inference.mp4 |
57.62MB |
| 4. Batch Normalization Inference.srt |
10.11KB |
| 4. Cross Entropy In Multi-Class Problems.mp4 |
55.93MB |
| 4. Cross Entropy In Multi-Class Problems.srt |
12.38KB |
| 4. Intuition Of Multi-Layer Perceptrons - Part 2.mp4 |
68.05MB |
| 4. Intuition Of Multi-Layer Perceptrons - Part 2.srt |
11.31KB |
| 4. L1 vs L2 Regularization - Part 1 - Gradient Descent.mp4 |
42.44MB |
| 4. L1 vs L2 Regularization - Part 1 - Gradient Descent.srt |
8.65KB |
| 4. Notes About Gradient Descent.mp4 |
29.69MB |
| 4. Notes About Gradient Descent.srt |
6.56KB |
| 4. Precision-Recall Curve.mp4 |
38.50MB |
| 4. Precision-Recall Curve.srt |
9.01KB |
| 4. Proof Perceptron Convergence Theorem - Part 2.mp4 |
22.93MB |
| 4. Proof Perceptron Convergence Theorem - Part 2.srt |
5.97KB |
| 4. Vectorization Of BackPropagation - Part 1.mp4 |
40.05MB |
| 4. Vectorization Of BackPropagation - Part 1.srt |
6.01KB |
| 4. Visualization Of The Perceptron Equation.mp4 |
27.12MB |
| 4. Visualization Of The Perceptron Equation.srt |
5.53KB |
| 5. Derivation Of Back Propagation Through Batch Normalization - Part (I).mp4 |
77.41MB |
| 5. Derivation Of Back Propagation Through Batch Normalization - Part (I).srt |
15.11KB |
| 5. L1 vs L2 Regularization -Part 2 - Numerical, Intuitive, And Graphical Comparison.mp4 |
107.01MB |
| 5. L1 vs L2 Regularization -Part 2 - Numerical, Intuitive, And Graphical Comparison.srt |
22.85KB |
| 5. More Notes And filling Up.mp4 |
68.25MB |
| 5. More Notes And filling Up.srt |
12.85KB |
| 5. Proof Perceptron Convergence Theorem - Part 3.mp4 |
48.07MB |
| 5. Proof Perceptron Convergence Theorem - Part 3.srt |
7.60KB |
| 5. Proof Weight Vector Is Perpendicular To The Decision Boundary.mp4 |
57.60MB |
| 5. Proof Weight Vector Is Perpendicular To The Decision Boundary.srt |
9.37KB |
| 5. ROC and AUC.mp4 |
86.58MB |
| 5. ROC and AUC.srt |
18.13KB |
| 5. The Softmax Activation Function.mp4 |
27.38MB |
| 5. The Softmax Activation Function.srt |
5.00KB |
| 5. The Vanishing Gradient Problem.mp4 |
46.87MB |
| 5. The Vanishing Gradient Problem.srt |
8.04KB |
| 5. The XOR Problem - Part 1.mp4 |
93.19MB |
| 5. The XOR Problem - Part 1.srt |
19.42KB |
| 5. Vectorization Of BackPropagation - Part 2.mp4 |
56.54MB |
| 5. Vectorization Of BackPropagation - Part 2.srt |
10.53KB |
| 6. BackPropagation Derivation For The Softmax Activation Function.mp4 |
107.45MB |
| 6. BackPropagation Derivation For The Softmax Activation Function.srt |
18.11KB |
| 6. Derivation Of Back Propagation Though Batch Normalization - Part 2.mp4 |
110.40MB |
| 6. Derivation Of Back Propagation Though Batch Normalization - Part 2.srt |
17.54KB |
| 6. Dropout ! - Intuition.mp4 |
68.73MB |
| 6. Dropout ! - Intuition.srt |
11.96KB |
| 6. Input Centering And Normalization - Part 1.mp4 |
25.23MB |
| 6. Input Centering And Normalization - Part 1.srt |
6.69KB |
| 6. More Visualization For The Perceptron Weights - I.mp4 |
66.69MB |
| 6. More Visualization For The Perceptron Weights - I.srt |
14.52KB |
| 6. Solved Example (III) Gradient Descent Convergence.mp4 |
66.31MB |
| 6. Solved Example (III) Gradient Descent Convergence.srt |
14.90KB |
| 6. The XOR Problem - Part 2.mp4 |
33.33MB |
| 6. The XOR Problem - Part 2.srt |
6.94KB |
| 6. Three Main Problems Of The Threshold Perceptron.mp4 |
30.16MB |
| 6. Three Main Problems Of The Threshold Perceptron.srt |
7.67KB |
| 6. Vectorization Of BackPropagation - Part 3.mp4 |
35.90MB |
| 6. Vectorization Of BackPropagation - Part 3.srt |
5.80KB |
| 7. Dropout vs Inverted Dropout.mp4 |
47.80MB |
| 7. Dropout vs Inverted Dropout.srt |
6.26KB |
| 7. Input Centering And Normalization - Part 2.mp4 |
40.33MB |
| 7. Input Centering And Normalization - Part 2.srt |
10.17KB |
| 7. More Visualization Of The Perceptron Weights - II.mp4 |
114.75MB |
| 7. More Visualization Of The Perceptron Weights - II.srt |
18.27KB |
| 7. MultiClass Classification And The Sigmoid Activation.mp4 |
92.16MB |
| 7. MultiClass Classification And The Sigmoid Activation.srt |
17.59KB |
| 7. Notes About Softmax.html |
1.55KB |
| 7. Solved Example (IIII) MLP With Linear Activations.mp4 |
26.41MB |
| 7. Solved Example (IIII) MLP With Linear Activations.srt |
4.52KB |
| 7. Vectorization Of BackPropagation - Part 4.mp4 |
20.10MB |
| 7. Vectorization Of BackPropagation - Part 4.srt |
3.36KB |
| 8. Activation Functions.mp4 |
18.00MB |
| 8. Activation Functions.srt |
4.84KB |
| 8. Dropout in a nutshell.html |
326B |
| 8. Vectorization Of BackPropagation - Part 5 - Batch Vectorization.mp4 |
76.11MB |
| 8. Vectorization Of BackPropagation - Part 5 - Batch Vectorization.srt |
15.62KB |
| 8. Vectorized Notation And The Weight Matrix.mp4 |
26.67MB |
| 8. Vectorized Notation And The Weight Matrix.srt |
3.15KB |
| 8. Weight Initialization - Part 1 - The Symmetry Problem.mp4 |
41.14MB |
| 8. Weight Initialization - Part 1 - The Symmetry Problem.srt |
9.97KB |
| 9. Cross-Validation How Do I Know I Am Overfitting Or Underfitting .mp4 |
50.68MB |
| 9. Cross-Validation How Do I Know I Am Overfitting Or Underfitting .srt |
13.52KB |
| 9. Graphical Representation Of A Neural Network.mp4 |
24.37MB |
| 9. Graphical Representation Of A Neural Network.srt |
6.16KB |
| 9. Weight Initialization - Part 2.mp4 |
42.08MB |
| 9. Weight Initialization - Part 2.srt |
9.93KB |
| TutsNode.com.txt |
63B |