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| 1. Artificial Neural Networks Section Introduction.mp4 |
33.48Мб |
| 1. Artificial Neural Networks Section Introduction.srt |
7.90Кб |
| 1. Custom Loss and Estimating Prediction Uncertainty.mp4 |
43.55Мб |
| 1. Custom Loss and Estimating Prediction Uncertainty.srt |
12.78Кб |
| 1. Deep Reinforcement Learning Section Introduction.mp4 |
40.66Мб |
| 1. Deep Reinforcement Learning Section Introduction.srt |
8.60Кб |
| 1. Embeddings.mp4 |
59.97Мб |
| 1. Embeddings.srt |
16.12Кб |
| 1. Facial Recognition Section Introduction.mp4 |
24.31Мб |
| 1. Facial Recognition Section Introduction.srt |
4.58Кб |
| 1. GAN Theory.mp4 |
92.11Мб |
| 1. GAN Theory.srt |
21.06Кб |
| 1. Gradient Descent.mp4 |
34.91Мб |
| 1. Gradient Descent.srt |
9.77Кб |
| 1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 |
150.67Мб |
| 1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt |
14.69Кб |
| 1. Intro to Google Colab, how to use a GPU or TPU for free.mp4 |
60.45Мб |
| 1. Intro to Google Colab, how to use a GPU or TPU for free.srt |
14.34Кб |
| 1. Links To Colab Notebooks.html |
7.24Кб |
| 1. Mean Squared Error.mp4 |
33.79Мб |
| 1. Mean Squared Error.srt |
11.21Кб |
| 1. Recommender Systems with Deep Learning Theory.mp4 |
64.75Мб |
| 1. Recommender Systems with Deep Learning Theory.srt |
13.71Кб |
| 1. Reinforcement Learning Stock Trader Introduction.mp4 |
28.82Мб |
| 1. Reinforcement Learning Stock Trader Introduction.srt |
6.84Кб |
| 1. Sequence Data.mp4 |
114.29Мб |
| 1. Sequence Data.srt |
29.57Кб |
| 1. Transfer Learning Theory.mp4 |
58.19Мб |
| 1. Transfer Learning Theory.srt |
10.70Кб |
| 1. Welcome.mp4 |
35.71Мб |
| 1. Welcome.srt |
5.70Кб |
| 1. What is Convolution (part 1).mp4 |
79.65Мб |
| 1. What is Convolution (part 1).srt |
20.13Кб |
| 1. What is Machine Learning.mp4 |
70.59Мб |
| 1. What is Machine Learning.srt |
18.45Кб |
| 1. What is the Appendix.mp4 |
16.38Мб |
| 1. What is the Appendix.srt |
3.75Кб |
| 10. CNN for CIFAR-10.mp4 |
56.72Мб |
| 10. CNN for CIFAR-10.srt |
9.25Кб |
| 10. Epsilon-Greedy.mp4 |
41.47Мб |
| 10. Epsilon-Greedy.srt |
7.42Кб |
| 10. Facial Recognition Section Summary.mp4 |
18.33Мб |
| 10. Facial Recognition Section Summary.srt |
4.39Кб |
| 10. GRU and LSTM (pt 2).mp4 |
50.56Мб |
| 10. GRU and LSTM (pt 2).srt |
14.97Кб |
| 10. Saving and Loading a Model.mp4 |
28.83Мб |
| 10. Saving and Loading a Model.srt |
6.61Кб |
| 11. A More Challenging Sequence.mp4 |
86.67Мб |
| 11. A More Challenging Sequence.srt |
10.66Кб |
| 11. A Short Neuroscience Primer.mp4 |
44.66Мб |
| 11. A Short Neuroscience Primer.srt |
12.27Кб |
| 11. Data Augmentation.mp4 |
44.52Мб |
| 11. Data Augmentation.srt |
12.52Кб |
| 11. Q-Learning.mp4 |
66.79Мб |
| 11. Q-Learning.srt |
17.91Кб |
| 12. Batch Normalization.mp4 |
23.44Мб |
| 12. Batch Normalization.srt |
6.57Кб |
| 12. Deep Q-Learning DQN (pt 1).mp4 |
60.24Мб |
| 12. Deep Q-Learning DQN (pt 1).srt |
16.43Кб |
| 12. How does a model learn.mp4 |
50.08Мб |
| 12. How does a model learn.srt |
13.76Кб |
| 12. RNN for Image Classification (Theory).mp4 |
32.26Мб |
| 12. RNN for Image Classification (Theory).srt |
5.99Кб |
| 13. Deep Q-Learning DQN (pt 2).mp4 |
52.22Мб |
| 13. Deep Q-Learning DQN (pt 2).srt |
13.21Кб |
| 13. Improving CIFAR-10 Results.mp4 |
77.42Мб |
| 13. Improving CIFAR-10 Results.srt |
12.79Кб |
| 13. Model With Logits.mp4 |
27.31Мб |
| 13. Model With Logits.srt |
5.32Кб |
| 13. RNN for Image Classification (Code).mp4 |
20.53Мб |
| 13. RNN for Image Classification (Code).srt |
3.28Кб |
| 14. How to Learn Reinforcement Learning.mp4 |
40.25Мб |
| 14. How to Learn Reinforcement Learning.srt |
7.62Кб |
| 14. Stock Return Predictions using LSTMs (pt 1).mp4 |
77.82Мб |
| 14. Stock Return Predictions using LSTMs (pt 1).srt |
15.96Кб |
| 14. Train Sets vs. Validation Sets vs. Test Sets.mp4 |
52.14Мб |
| 14. Train Sets vs. Validation Sets vs. Test Sets.srt |
14.26Кб |
| 15. Stock Return Predictions using LSTMs (pt 2).mp4 |
43.22Мб |
| 15. Stock Return Predictions using LSTMs (pt 2).srt |
6.85Кб |
| 16. Stock Return Predictions using LSTMs (pt 3).mp4 |
71.07Мб |
| 16. Stock Return Predictions using LSTMs (pt 3).srt |
14.37Кб |
| 17. Other Ways to Forecast.mp4 |
28.27Мб |
| 17. Other Ways to Forecast.srt |
7.18Кб |
| 2. Binary Cross Entropy.mp4 |
23.68Мб |
| 2. Binary Cross Entropy.srt |
7.26Кб |
| 2. Data and Environment.mp4 |
55.69Мб |
| 2. Data and Environment.srt |
15.69Кб |
| 2. Elements of a Reinforcement Learning Problem.mp4 |
104.93Мб |
| 2. Elements of a Reinforcement Learning Problem.srt |
26.23Кб |
| 2. Estimating Prediction Uncertainty Code.mp4 |
42.75Мб |
| 2. Estimating Prediction Uncertainty Code.srt |
8.82Кб |
| 2. Forecasting.mp4 |
48.70Мб |
| 2. Forecasting.srt |
13.21Кб |
| 2. Forward Propagation.mp4 |
47.10Мб |
| 2. Forward Propagation.srt |
12.20Кб |
| 2. GAN Code Preparation.mp4 |
28.08Мб |
| 2. GAN Code Preparation.srt |
8.51Кб |
| 2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 |
105.66Мб |
| 2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt |
31.63Кб |
| 2. Links to VIP Notebooks.html |
256б |
| 2. Neural Networks with Embeddings.mp4 |
15.63Мб |
| 2. Neural Networks with Embeddings.srt |
4.51Кб |
| 2. Overview and Outline.mp4 |
79.66Мб |
| 2. Overview and Outline.srt |
17.74Кб |
| 2. Recommender Systems with Deep Learning Code Preparation.mp4 |
40.10Мб |
| 2. Recommender Systems with Deep Learning Code Preparation.srt |
12.67Кб |
| 2. Regression Basics.mp4 |
73.02Мб |
| 2. Regression Basics.srt |
20.08Кб |
| 2. Siamese Networks.mp4 |
50.52Мб |
| 2. Siamese Networks.srt |
12.81Кб |
| 2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).mp4 |
21.67Мб |
| 2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).srt |
5.16Кб |
| 2. Stochastic Gradient Descent.mp4 |
22.98Мб |
| 2. Stochastic Gradient Descent.srt |
5.40Кб |
| 2. Uploading your own data to Google Colab.mp4 |
90.53Мб |
| 2. Uploading your own data to Google Colab.srt |
14.47Кб |
| 2. What is Convolution (part 2).mp4 |
24.49Мб |
| 2. What is Convolution (part 2).srt |
7.25Кб |
| 2. Windows-Focused Environment Setup 2018.mp4 |
180.67Мб |
| 2. Windows-Focused Environment Setup 2018.srt |
19.96Кб |
| 3. Autoregressive Linear Model for Time Series Prediction.mp4 |
81.19Мб |
| 3. Autoregressive Linear Model for Time Series Prediction.srt |
14.68Кб |
| 3. Categorical Cross Entropy.mp4 |
31.74Мб |
| 3. Categorical Cross Entropy.srt |
9.62Кб |
| 3. Code Outline.mp4 |
23.86Мб |
| 3. Code Outline.srt |
5.82Кб |
| 3. GAN Code.mp4 |
61.37Мб |
| 3. GAN Code.srt |
10.66Кб |
| 3. How to Code Yourself (part 1).mp4 |
71.87Мб |
| 3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 |
167.32Мб |
| 3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.srt |
32.01Кб |
| 3. Large Datasets.mp4 |
41.26Мб |
| 3. Large Datasets.srt |
9.09Кб |
| 3. Momentum.mp4 |
34.25Мб |
| 3. Momentum.srt |
7.84Кб |
| 3. Recommender Systems with Deep Learning Code (pt 1).mp4 |
69.58Мб |
| 3. Recommender Systems with Deep Learning Code (pt 1).srt |
10.92Кб |
| 3. Regression Code Preparation.mp4 |
45.53Мб |
| 3. Regression Code Preparation.srt |
16.37Кб |
| 3. Replay Buffer.mp4 |
24.97Мб |
| 3. Replay Buffer.srt |
6.94Кб |
| 3. States, Actions, Rewards, Policies.mp4 |
44.12Мб |
| 3. States, Actions, Rewards, Policies.srt |
11.32Кб |
| 3. Text Preprocessing (pt 1).mp4 |
52.29Мб |
| 3. Text Preprocessing (pt 1).srt |
17.87Кб |
| 3. The Geometrical Picture.mp4 |
56.42Мб |
| 3. The Geometrical Picture.srt |
11.51Кб |
| 3. What is Convolution (part 3).mp4 |
28.70Мб |
| 3. What is Convolution (part 3).srt |
8.01Кб |
| 3. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4 |
44.39Мб |
| 3. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.srt |
12.07Кб |
| 3. Where to get the Code.mp4 |
30.17Мб |
| 3. Where to get the Code.srt |
7.60Кб |
| 4. 2 Approaches to Transfer Learning.mp4 |
21.79Мб |
| 4. 2 Approaches to Transfer Learning.srt |
5.96Кб |
| 4. Activation Functions.mp4 |
89.24Мб |
| 4. Activation Functions.srt |
22.64Кб |
| 4. Convolution on Color Images.mp4 |
76.38Мб |
| 4. Convolution on Color Images.srt |
20.84Кб |
| 4. How to Code Yourself (part 2).mp4 |
49.15Мб |
| 4. How to Code Yourself (part 2).srt |
12.98Кб |
| 4. Loading in the data.mp4 |
35.07Мб |
| 4. Loading in the data.srt |
6.89Кб |
| 4. Markov Decision Processes (MDPs).mp4 |
50.51Мб |
| 4. Markov Decision Processes (MDPs).srt |
12.65Кб |
| 4. Program Design and Layout.mp4 |
26.86Мб |
| 4. Program Design and Layout.srt |
8.64Кб |
| 4. Proof that the Linear Model Works.mp4 |
17.91Мб |
| 4. Proof that the Linear Model Works.srt |
4.56Кб |
| 4. Recommender Systems with Deep Learning Code (pt 2).mp4 |
76.87Мб |
| 4. Recommender Systems with Deep Learning Code (pt 2).srt |
17.43Кб |
| 4. Regression Notebook.mp4 |
71.93Мб |
| 4. Regression Notebook.srt |
17.48Кб |
| 4. Text Preprocessing (pt 2).mp4 |
44.42Мб |
| 4. Text Preprocessing (pt 2).srt |
15.31Кб |
| 4. Variable and Adaptive Learning Rates.mp4 |
34.85Мб |
| 4. Variable and Adaptive Learning Rates.srt |
15.15Кб |
| 5. Adam.mp4 |
38.90Мб |
| 5. Adam.srt |
13.53Кб |
| 5. CNN Architecture.mp4 |
89.53Мб |
| 5. CNN Architecture.srt |
27.77Кб |
| 5. Code pt 1.mp4 |
66.34Мб |
| 5. Code pt 1.srt |
12.12Кб |
| 5. Moore's Law.mp4 |
30.63Мб |
| 5. Moore's Law.srt |
9.14Кб |
| 5. Multiclass Classification.mp4 |
48.69Мб |
| 5. Multiclass Classification.srt |
12.20Кб |
| 5. Proof that using Jupyter Notebook is the same as not using it.mp4 |
69.50Мб |
| 5. Proof that using Jupyter Notebook is the same as not using it.srt |
14.22Кб |
| 5. Recurrent Neural Networks.mp4 |
92.61Мб |
| 5. Recurrent Neural Networks.srt |
25.69Кб |
| 5. Splitting the data into train and test.mp4 |
26.30Мб |
| 5. Splitting the data into train and test.srt |
5.09Кб |
| 5. Text Preprocessing (pt 3).mp4 |
47.74Мб |
| 5. Text Preprocessing (pt 3).srt |
9.43Кб |
| 5. The Return.mp4 |
23.42Мб |
| 5. The Return.srt |
6.26Кб |
| 5. Transfer Learning Code (pt 1).mp4 |
77.78Мб |
| 5. Transfer Learning Code (pt 1).srt |
11.61Кб |
| 5. VIP Making Predictions with a Trained Recommender Model.mp4 |
32.74Мб |
| 5. VIP Making Predictions with a Trained Recommender Model.srt |
6.01Кб |
| 6. CNN Code Preparation (part 1).mp4 |
76.74Мб |
| 6. CNN Code Preparation (part 1).srt |
22.83Кб |
| 6. Code pt 2.mp4 |
69.98Мб |
| 6. Code pt 2.srt |
11.75Кб |
| 6. Converting the data into pairs.mp4 |
30.38Мб |
| 6. Converting the data into pairs.srt |
5.79Кб |
| 6. How to Represent Images.mp4 |
75.43Мб |
| 6. How to Represent Images.srt |
15.30Кб |
| 6. How to Succeed in this Course (Long Version).mp4 |
35.25Мб |
| 6. How to Succeed in this Course (Long Version).srt |
14.61Кб |
| 6. Moore's Law Notebook.mp4 |
78.92Мб |
| 6. Moore's Law Notebook.srt |
15.85Кб |
| 6. RNN Code Preparation.mp4 |
55.31Мб |
| 6. RNN Code Preparation.srt |
17.63Кб |
| 6. Text Classification with LSTMs.mp4 |
65.05Мб |
| 6. Text Classification with LSTMs.srt |
10.26Кб |
| 6. Transfer Learning Code (pt 2).mp4 |
56.32Мб |
| 6. Transfer Learning Code (pt 2).srt |
8.76Кб |
| 6. Value Functions and the Bellman Equation.mp4 |
47.72Мб |
| 6. Value Functions and the Bellman Equation.srt |
12.51Кб |
| 7. CNN Code Preparation (part 2).mp4 |
36.72Мб |
| 7. CNN Code Preparation (part 2).srt |
10.43Кб |
| 7. CNNs for Text.mp4 |
58.70Мб |
| 7. CNNs for Text.srt |
14.88Кб |
| 7. Code Preparation (ANN).mp4 |
67.55Мб |
| 7. Code Preparation (ANN).srt |
19.93Кб |
| 7. Code pt 3.mp4 |
58.59Мб |
| 7. Code pt 3.srt |
8.44Кб |
| 7. Generating Generators.mp4 |
32.44Мб |
| 7. Generating Generators.srt |
5.73Кб |
| 7. Linear Classification Basics.mp4 |
67.22Мб |
| 7. Linear Classification Basics.srt |
19.84Кб |
| 7. RNN for Time Series Prediction.mp4 |
71.85Мб |
| 7. RNN for Time Series Prediction.srt |
9.88Кб |
| 7. What does it mean to “learn”.mp4 |
32.51Мб |
| 7. What does it mean to “learn”.srt |
8.92Кб |
| 7. What order should I take your courses in (part 1).mp4 |
79.59Мб |
| 7. What order should I take your courses in (part 1).srt |
16.12Кб |
| 8. ANN for Image Classification.mp4 |
106.33Мб |
| 8. ANN for Image Classification.srt |
22.58Кб |
| 8. Classification Code Preparation.mp4 |
26.54Мб |
| 8. Classification Code Preparation.srt |
9.36Кб |
| 8. CNN Code Preparation (part 3).mp4 |
33.69Мб |
| 8. CNN Code Preparation (part 3).srt |
7.18Кб |
| 8. Code pt 4.mp4 |
52.32Мб |
| 8. Code pt 4.srt |
8.23Кб |
| 8. Creating the model and loss.mp4 |
29.38Мб |
| 8. Creating the model and loss.srt |
5.38Кб |
| 8. Paying Attention to Shapes.mp4 |
56.41Мб |
| 8. Paying Attention to Shapes.srt |
11.00Кб |
| 8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4 |
42.62Мб |
| 8. Solving the Bellman Equation with Reinforcement Learning (pt 1).srt |
12.65Кб |
| 8. Text Classification with CNNs.mp4 |
39.33Мб |
| 8. Text Classification with CNNs.srt |
5.63Кб |
| 8. What order should I take your courses in (part 2).mp4 |
108.23Мб |
| 8. What order should I take your courses in (part 2).srt |
23.01Кб |
| 9. Accuracy and imbalanced classes.mp4 |
51.09Мб |
| 9. Accuracy and imbalanced classes.srt |
9.52Кб |
| 9. ANN for Regression.mp4 |
80.18Мб |
| 9. ANN for Regression.srt |
13.01Кб |
| 9. BONUS Where to get discount coupons and FREE deep learning material.mp4 |
37.81Мб |
| 9. BONUS Where to get discount coupons and FREE deep learning material.srt |
7.87Кб |
| 9. Classification Notebook.mp4 |
78.28Мб |
| 9. Classification Notebook.srt |
14.59Кб |
| 9. CNN for Fashion MNIST.mp4 |
74.46Мб |
| 9. CNN for Fashion MNIST.srt |
13.45Кб |
| 9. GRU and LSTM (pt 1).mp4 |
76.07Мб |
| 9. GRU and LSTM (pt 1).srt |
21.11Кб |
| 9. Reinforcement Learning Stock Trader Discussion.mp4 |
17.22Мб |
| 9. Reinforcement Learning Stock Trader Discussion.srt |
4.39Кб |
| 9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4 |
57.02Мб |
| 9. Solving the Bellman Equation with Reinforcement Learning (pt 2).srt |
14.88Кб |
| 9. VIP Making Predictions with a Trained NLP Model.mp4 |
48.81Мб |
| 9. VIP Making Predictions with a Trained NLP Model.srt |
9.13Кб |
| CourseRecap-Click For More Courses!!.url |
50б |
| CourseRecap-Click For More Courses!!.url |
50б |
| READ_ME.txt |
404б |
| READ_ME.txt |
404б |