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| [TGx]Downloaded from torrentgalaxy.to .txt |
585б |
| 0 |
1009б |
| 1 |
289.10Кб |
| 1. Decision Trees - Theory.mp4 |
138.76Мб |
| 1. Decision Trees - Theory.srt |
15.24Кб |
| 1. Fashion Clothing Recognition.mp4 |
156.69Мб |
| 1. Fashion Clothing Recognition.srt |
22.17Кб |
| 1. Introduction.mp4 |
109.11Мб |
| 1. Introduction.mp4 |
100.29Мб |
| 1. Introduction.srt |
12.00Кб |
| 1. Introduction.srt |
11.56Кб |
| 1. K-Means Algorithm (Part 1).mp4 |
99.93Мб |
| 1. K-Means Algorithm (Part 1).srt |
14.26Кб |
| 1. What is TensorFlow 2 Preview.mp4 |
86.90Мб |
| 1. What is TensorFlow 2 Preview.srt |
12.58Кб |
| 10 |
157.84Кб |
| 11 |
564.54Кб |
| 12 |
775.31Кб |
| 13 |
354.26Кб |
| 14 |
149.49Кб |
| 15 |
912.28Кб |
| 16 |
464.97Кб |
| 17 |
749.47Кб |
| 18 |
996.57Кб |
| 19 |
859.51Кб |
| 2 |
914.00Кб |
| 2. Basics of TensorFlow.mp4 |
74.42Мб |
| 2. Basics of TensorFlow.srt |
11.58Кб |
| 2. CIFAR 10 and CNN.mp4 |
83.59Мб |
| 2. CIFAR 10 and CNN.srt |
12.72Кб |
| 2. Convolution in CNN (part1).mp4 |
137.27Мб |
| 2. Convolution in CNN (part1).srt |
16.54Кб |
| 2. Decision Trees - Implementation.mp4 |
60.93Мб |
| 2. Decision Trees - Implementation.srt |
10.10Кб |
| 2. Gates and Forward Propagation.mp4 |
104.27Мб |
| 2. Gates and Forward Propagation.srt |
11.96Кб |
| 2. K-Means Algorithm (Part 2).mp4 |
103.16Мб |
| 2. K-Means Algorithm (Part 2).srt |
12.90Кб |
| 20 |
724.16Кб |
| 21 |
66.69Кб |
| 22 |
562.52Кб |
| 23 |
37.14Кб |
| 24 |
695.91Кб |
| 25 |
104.98Кб |
| 26 |
419.92Кб |
| 27 |
926.05Кб |
| 28 |
443.06Кб |
| 29 |
880.21Кб |
| 3 |
829.65Кб |
| 3. Cats vs Dogs.mp4 |
289.51Мб |
| 3. Cats vs Dogs.srt |
39.83Кб |
| 3. Centroid Initialization.mp4 |
66.26Мб |
| 3. Centroid Initialization.srt |
8.73Кб |
| 3. Complex Decision Boundaries.mp4 |
111.65Мб |
| 3. Complex Decision Boundaries.srt |
13.56Кб |
| 3. Convolution in CNN (part2).mp4 |
131.71Мб |
| 3. Convolution in CNN (part2).srt |
14.99Кб |
| 3. Graphs.mp4 |
112.24Мб |
| 3. Graphs.srt |
14.95Кб |
| 3. Linear Regression - Theory.mp4 |
144.13Мб |
| 3. Linear Regression - Theory.srt |
17.35Кб |
| 30 |
597.79Кб |
| 31 |
15.98Кб |
| 32 |
760.44Кб |
| 33 |
116.63Кб |
| 34 |
69.48Кб |
| 35 |
307.30Кб |
| 36 |
781.31Кб |
| 37 |
42.16Кб |
| 38 |
243.19Кб |
| 4 |
651.40Кб |
| 4. Action Recognition.mp4 |
82.10Мб |
| 4. Action Recognition.srt |
10.35Кб |
| 4. Automatic Differentiation.mp4 |
77.57Мб |
| 4. Automatic Differentiation.srt |
11.32Кб |
| 4. Backpropagation.mp4 |
147.19Мб |
| 4. Backpropagation.srt |
20.70Кб |
| 4. K-Means ++.mp4 |
90.32Мб |
| 4. K-Means ++.srt |
12.61Кб |
| 4. Layers of CNN.mp4 |
113.85Мб |
| 4. Layers of CNN.srt |
12.99Кб |
| 4. Linear Regression - Implementation.mp4 |
104.03Мб |
| 4. Linear Regression - Implementation.srt |
17.04Кб |
| 5 |
895.90Кб |
| 5. Digit Classification.mp4 |
93.96Мб |
| 5. Digit Classification.srt |
11.86Кб |
| 5. Gradient Descent Type and Softmax.mp4 |
62.89Мб |
| 5. Gradient Descent Type and Softmax.srt |
7.75Кб |
| 5. Keras and TensorFlow.mp4 |
66.98Мб |
| 5. Keras and TensorFlow.srt |
7.78Кб |
| 5. Logistic Regression - Theory.mp4 |
107.55Мб |
| 5. Logistic Regression - Theory.srt |
11.73Кб |
| 5. Number of Clusters.mp4 |
31.76Мб |
| 5. Number of Clusters.srt |
4.56Кб |
| 6 |
245.25Кб |
| 6. Digit Classification.mp4 |
144.36Мб |
| 6. Digit Classification.srt |
21.08Кб |
| 6. Famous CNN Architectures.mp4 |
96.45Мб |
| 6. Famous CNN Architectures.srt |
12.17Кб |
| 6. Intro to Machine Learning.mp4 |
112.45Мб |
| 6. Intro to Machine Learning.srt |
11.78Кб |
| 6. K-Means Implementation.mp4 |
50.70Мб |
| 6. K-Means Implementation.srt |
7.39Кб |
| 6. Logistic Regression - Implementation.mp4 |
117.32Мб |
| 6. Logistic Regression - Implementation.srt |
17.92Кб |
| 7 |
743.52Кб |
| 7. Overfitting and Regularization.mp4 |
76.14Мб |
| 7. Overfitting and Regularization.srt |
8.99Кб |
| 7. Principal Component Analysis.mp4 |
109.85Мб |
| 7. Principal Component Analysis.srt |
12.60Кб |
| 7. Types of Supervised Learning.mp4 |
27.57Мб |
| 7. Types of Supervised Learning.srt |
3.83Кб |
| 8 |
301.44Кб |
| 8. Facial Recognition using PCA.mp4 |
149.11Мб |
| 8. Facial Recognition using PCA.srt |
19.40Кб |
| 8. Model Evaluation - Theory.mp4 |
46.24Мб |
| 8. Model Evaluation - Theory.srt |
5.24Кб |
| 9 |
701.16Кб |
| 9. Model Evaluation - Implementation.mp4 |
32.96Мб |
| 9. Model Evaluation - Implementation.srt |
3.97Кб |
| TutsNode.com.txt |
63б |