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| [TGx]Downloaded from torrentgalaxy.to .txt |
585б |
| 0 |
72б |
| 1 |
40б |
| 1. CNN Transfer Learning.mp4 |
80.69Мб |
| 1. CNN Transfer Learning.srt |
18.60Кб |
| 1. Concept of Machine Learning.mp4 |
44.62Мб |
| 1. Concept of Machine Learning.srt |
11.38Кб |
| 1. Describe Artificial Intelligence and Machine Learning and Deep Learning.mp4 |
20.77Мб |
| 1. Describe Artificial Intelligence and Machine Learning and Deep Learning.srt |
4.91Кб |
| 1. Google Colab Introduction.mp4 |
14.91Мб |
| 1. Google Colab Introduction.srt |
6.02Кб |
| 1. Introduction to Autoencoders.mp4 |
71.44Мб |
| 1. Introduction to Autoencoders.srt |
18.67Кб |
| 1. Neural Style Transfer.mp4 |
32.92Мб |
| 1. Neural Style Transfer.srt |
6.39Кб |
| 1. Python for Data Analysis- Numpy.mp4 |
56.39Мб |
| 1. Python for Data Analysis- Numpy.srt |
18.30Кб |
| 1. RNN INTRODUCTION.mp4 |
55.81Мб |
| 1. RNN INTRODUCTION.srt |
18.53Кб |
| 1. What is CNN.mp4 |
24.68Мб |
| 1. What is CNN.srt |
8.33Кб |
| 1. What is GANs.mp4 |
44.30Мб |
| 1. What is GANs.srt |
15.87Кб |
| 1. What is Keras.mp4 |
27.46Мб |
| 1. What is Keras.srt |
6.09Кб |
| 10 |
935.89Кб |
| 10. Matplotlib Histogram.mp4 |
15.65Мб |
| 10. Matplotlib Histogram.srt |
3.77Кб |
| 10. Tensorflow Introduction.mp4 |
44.44Мб |
| 10. Tensorflow Introduction.srt |
14.23Кб |
| 11 |
926.95Кб |
| 11. Eager Execution.mp4 |
18.86Мб |
| 11. Eager Execution.srt |
6.10Кб |
| 11. Matplotlib Scatter Plot.mp4 |
18.90Мб |
| 11. Matplotlib Scatter Plot.srt |
5.92Кб |
| 12 |
441.51Кб |
| 12. Matplotlib Area Plot.mp4 |
16.18Мб |
| 12. Matplotlib Area Plot.srt |
4.31Кб |
| 13 |
298.92Кб |
| 13. Matplotlib Pie Chart.mp4 |
9.77Мб |
| 13. Matplotlib Pie Chart.srt |
3.10Кб |
| 14 |
592.69Кб |
| 14. Matplotlib Subplots.mp4 |
12.70Мб |
| 14. Matplotlib Subplots.srt |
4.87Кб |
| 15 |
375.43Кб |
| 16 |
108.64Кб |
| 17 |
670.38Кб |
| 18 |
623.00Кб |
| 19 |
195.08Кб |
| 2 |
1.00Кб |
| 2.1 Autoencoder_Sukanya.ipynb |
170.18Кб |
| 2.1 Neural_Style_Transfer.ipynb |
25.85Мб |
| 2. Anaconda Installation.mp4 |
33.80Мб |
| 2. Anaconda Installation.srt |
8.14Кб |
| 2. CIFAR 10.mp4 |
59.35Мб |
| 2. CIFAR 10.srt |
14.90Кб |
| 2. Data Augmentation.mp4 |
97.37Мб |
| 2. Data Augmentation.srt |
21.38Кб |
| 2. DCGAN INTRODUCTION.mp4 |
32.00Мб |
| 2. DCGAN INTRODUCTION.srt |
6.83Кб |
| 2. implementation of autoencoder.mp4 |
65.71Мб |
| 2. implementation of autoencoder.srt |
15.97Кб |
| 2. Introduction to Neural Network.mp4 |
67.09Мб |
| 2. Introduction to Neural Network.srt |
20.51Кб |
| 2. LSTM.mp4 |
38.73Мб |
| 2. LSTM.srt |
13.15Кб |
| 2. Neural Style Transfer Implementation part 1.mp4 |
87.89Мб |
| 2. Neural Style Transfer Implementation part 1.srt |
15.78Кб |
| 2. Pandas Series.mp4 |
49.45Мб |
| 2. Pandas Series.srt |
16.13Кб |
| 2. What is Supervised Machine Learning and Linear Regression Algorithm.mp4 |
42.02Мб |
| 2. What is Supervised Machine Learning and Linear Regression Algorithm.srt |
8.51Кб |
| 2. Working of CNN.mp4 |
51.20Мб |
| 2. Working of CNN.srt |
17.47Кб |
| 20 |
598.29Кб |
| 21 |
816.68Кб |
| 22 |
567.87Кб |
| 23 |
124.09Кб |
| 24 |
850.82Кб |
| 25 |
102.76Кб |
| 26 |
490.57Кб |
| 27 |
391.16Кб |
| 28 |
480.57Кб |
| 29 |
573.22Кб |
| 3 |
1.05Кб |
| 3.1 DCGAN.ipynb |
214.37Кб |
| 3.1 Fashion_MNIST.ipynb |
328.08Кб |
| 3.1 mnist_digits.ipynb |
131.81Кб |
| 3. DCGAN Project.mp4 |
86.74Мб |
| 3. DCGAN Project.srt |
17.27Кб |
| 3. Fashion MNIST Part 1.mp4 |
66.57Мб |
| 3. Fashion MNIST Part 1.srt |
15.92Кб |
| 3. Jupyter Notebook.mp4 |
13.99Мб |
| 3. Jupyter Notebook.srt |
5.09Кб |
| 3. MNIST digit classification.mp4 |
69.09Мб |
| 3. MNIST digit classification.srt |
17.19Кб |
| 3. Neural Style Transfer Implementation part 2.mp4 |
76.32Мб |
| 3. Neural Style Transfer Implementation part 2.srt |
11.98Кб |
| 3. Pandas DataFrames.mp4 |
44.53Мб |
| 3. Pandas DataFrames.srt |
11.47Кб |
| 3. Text classification.mp4 |
71.53Мб |
| 3. Text classification.srt |
17.70Кб |
| 3. Types of Classification Problem.mp4 |
28.89Мб |
| 3. Types of Classification Problem.srt |
10.23Кб |
| 3. What is UnSupervised Machine Learning.mp4 |
47.17Мб |
| 3. What is UnSupervised Machine Learning.srt |
11.03Кб |
| 30 |
718.07Кб |
| 31 |
1002.84Кб |
| 32 |
324.24Кб |
| 33 |
279.44Кб |
| 34 |
884.32Кб |
| 35 |
959.06Кб |
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649.04Кб |
| 37 |
264.08Кб |
| 38 |
204.28Кб |
| 39 |
559.65Кб |
| 4 |
1.28Кб |
| 4.1 Copy_of_CNN_DOG_CAT_Colab.ipynb |
3.18Мб |
| 4. Activation Function part 1.mp4 |
46.90Мб |
| 4. Activation Function part 1.srt |
19.82Кб |
| 4. cat dog classification.mp4 |
79.59Мб |
| 4. cat dog classification.srt |
16.39Кб |
| 4. Fashion MNIST Part 2.mp4 |
65.42Мб |
| 4. Fashion MNIST Part 2.srt |
13.60Кб |
| 4. Grouping and Filtering.mp4 |
35.37Мб |
| 4. Grouping and Filtering.srt |
9.33Кб |
| 4. practical approach to word embedding.mp4 |
38.14Мб |
| 4. practical approach to word embedding.srt |
12.18Кб |
| 40 |
82.36Кб |
| 41 |
659б |
| 42 |
510.65Кб |
| 43 |
113.37Кб |
| 44 |
556.74Кб |
| 45 |
142.80Кб |
| 46 |
154.08Кб |
| 47 |
55.94Кб |
| 48 |
58.28Кб |
| 49 |
329.87Кб |
| 5 |
100.41Кб |
| 5. Activation Function part 2.mp4 |
37.06Мб |
| 5. Activation Function part 2.srt |
15.17Кб |
| 5. Bidirectional neural network.mp4 |
19.99Мб |
| 5. Bidirectional neural network.srt |
5.20Кб |
| 5. cat dog classification 2.mp4 |
55.42Мб |
| 5. cat dog classification 2.srt |
11.42Кб |
| 5. Fashion MNIST Part 3.mp4 |
61.63Мб |
| 5. Fashion MNIST Part 3.srt |
14.66Кб |
| 5. Slicing and Sorting.mp4 |
26.86Мб |
| 5. Slicing and Sorting.srt |
7.65Кб |
| 50 |
474.47Кб |
| 51 |
238.09Кб |
| 52 |
12.67Кб |
| 53 |
103.12Кб |
| 54 |
142.55Кб |
| 55 |
839.30Кб |
| 56 |
353.73Кб |
| 57 |
89.94Кб |
| 58 |
13.62Кб |
| 59 |
310.38Кб |
| 6 |
699.96Кб |
| 6. facial expression recognition 1.mp4 |
83.59Мб |
| 6. facial expression recognition 1.srt |
18.00Кб |
| 6. Forward Propogation.mp4 |
24.95Мб |
| 6. Forward Propogation.srt |
7.78Кб |
| 6. Pandas Missing Values.mp4 |
47.88Мб |
| 6. Pandas Missing Values.srt |
11.69Кб |
| 60 |
237.27Кб |
| 7 |
20.29Кб |
| 7.1 Copy_of_Facial_Expression_Training.ipynb |
535.69Кб |
| 7. Back Propogation.mp4 |
33.45Мб |
| 7. Back Propogation.srt |
8.37Кб |
| 7. facial expression recognition 2.mp4 |
34.74Мб |
| 7. facial expression recognition 2.srt |
5.84Кб |
| 7. Pandas Aggregation Functions.mp4 |
29.50Мб |
| 7. Pandas Aggregation Functions.srt |
7.98Кб |
| 8 |
478.03Кб |
| 8. Chain Rule.mp4 |
24.54Мб |
| 8. Chain Rule.srt |
7.99Кб |
| 8. leaf diseases 1.mp4 |
73.98Мб |
| 8. leaf diseases 1.srt |
14.77Кб |
| 8. Matplotlib Introduction.mp4 |
45.52Мб |
| 8. Matplotlib Introduction.srt |
13.67Кб |
| 9 |
571.41Кб |
| 9. Gradient Descent.mp4 |
60.89Мб |
| 9. Gradient Descent.srt |
12.53Кб |
| 9. leaf diseases 2.mp4 |
40.68Мб |
| 9. leaf diseases 2.srt |
9.08Кб |
| 9. Matplotlib Bar Graphs.mp4 |
24.94Мб |
| 9. Matplotlib Bar Graphs.srt |
5.71Кб |
| TutsNode.com.txt |
63б |