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种子名称： [FreeCourseLab.com] Udemy - Zero to Deep Learning™ with Python and Keras
文件类型： 视频
文件数目： 142个文件
文件大小： 1.86 GB
收录时间： 2019-9-17 10:31
已经下载： 3次
资源热度： 132
最近下载： 2024-11-5 20:56

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[FreeCourseLab.com] Udemy - Zero to Deep Learning™ with Python and Keras.torrent

1. Welcome to the course!/1. Welcome to the course!.mp427.38MB

1. Welcome to the course!/2. Introduction.mp433.87MB

1. Welcome to the course!/3. Real world applications of deep learning.mp423.61MB

1. Welcome to the course!/4. Download and install Anaconda.mp425.6MB

1. Welcome to the course!/5. Installation Video Guide.mp461.14MB

1. Welcome to the course!/7. Course Folder Walkthrough.mp419.24MB

1. Welcome to the course!/8. Your first deep learning model.mp432.9MB

2. Data/1. Section 2 Intro.mp422.25MB

2. Data/10. Exercise 1 Solution.mp49.42MB

2. Data/11. Exercise 2 Presentation.mp41.92MB

2. Data/12. Exercise 2 Solution.mp413.52MB

2. Data/13. Exercise 3 Presentation.mp41.74MB

2. Data/14. Exercise 3 Solution.mp47.15MB

2. Data/15. Exercise 4 Presentation.mp41.51MB

2. Data/16. Exercise 4 Solution.mp44.2MB

2. Data/17. Exercise 5 Presentation.mp42.12MB

2. Data/18. Exercise 5 Solution.mp47.81MB

2. Data/2. Tabular data.mp411.74MB

2. Data/3. Data exploration with Pandas code along.mp430.94MB

2. Data/4. Visual data Exploration.mp49.15MB

2. Data/5. Plotting with Matplotlib.mp432.85MB

2. Data/6. Unstructured Data.mp411.33MB

2. Data/7. Images and Sound in Jupyter.mp414.02MB

2. Data/8. Feature Engineering.mp45.82MB

2. Data/9. Exercise 1 Presentation.mp43.25MB

3. Machine Learning/1. Section 3 Intro.mp438.97MB

3. Machine Learning/10. Evaluating Performance code along.mp410.35MB

3. Machine Learning/11. Classification.mp414.2MB

3. Machine Learning/12. Classification code along.mp422.87MB

3. Machine Learning/13. Overfitting.mp49.39MB

3. Machine Learning/14. Cross Validation.mp412.38MB

3. Machine Learning/15. Cross Validation code along.mp49.71MB

3. Machine Learning/16. Confusion matrix.mp411.28MB

3. Machine Learning/17. Confusion Matrix code along.mp48.65MB

3. Machine Learning/18. Feature Preprocessing code along.mp416.01MB

3. Machine Learning/19. Exercise 1 Presentation.mp46.45MB

3. Machine Learning/2. Machine Learning Problems.mp49.31MB

3. Machine Learning/20. Exercise 1 solution.mp437.31MB

3. Machine Learning/21. Exercise 2 Presentation.mp47.4MB

3. Machine Learning/22. Exercise 2 solution.mp443.21MB

3. Machine Learning/3. Supervised Learning.mp410.42MB

3. Machine Learning/4. Linear Regression.mp49.77MB

3. Machine Learning/5. Cost Function.mp46.01MB

3. Machine Learning/6. Cost Function code along.mp417.9MB

3. Machine Learning/7. Finding the best model.mp45.1MB

3. Machine Learning/8. Linear Regression code along.mp439.87MB

3. Machine Learning/9. Evaluating Performance.mp49.04MB

4. Deep Learning Intro/1. Section 4 Intro.mp430.93MB

4. Deep Learning Intro/10. Exercise 1 Presentation.mp44.75MB

4. Deep Learning Intro/11. Exercise 1 Solution.mp424.77MB

4. Deep Learning Intro/12. Exercise 2 Presentation.mp43.03MB

4. Deep Learning Intro/13. Exercise 2 Solution.mp425.2MB

4. Deep Learning Intro/14. Exercise 3 Presentation.mp42.82MB

4. Deep Learning Intro/15. Exercise 3 Solution.mp420.61MB

4. Deep Learning Intro/16. Exercise 4 Presentation.mp41.93MB

4. Deep Learning Intro/17. Exercise 4 Solution.mp413.6MB

4. Deep Learning Intro/2. Deep Learning successes.mp410.15MB

4. Deep Learning Intro/3. Neural Networks.mp49.91MB

4. Deep Learning Intro/4. Deeper Networks.mp48.47MB

4. Deep Learning Intro/5. Neural Networks code along.mp421.11MB

4. Deep Learning Intro/6. Multiple Outputs.mp410.32MB

4. Deep Learning Intro/7. Multiclass classification code along.mp433.94MB

4. Deep Learning Intro/8. Activation Functions.mp48.51MB

4. Deep Learning Intro/9. Feed forward.mp49.98MB

5. Gradient Descent/1. Section 5 Intro.mp430.76MB

5. Gradient Descent/10. Learning Rate code along.mp433.17MB

5. Gradient Descent/11. Gradient Descent.mp46.42MB

5. Gradient Descent/12. Gradient Descent code along.mp413.2MB

5. Gradient Descent/13. EWMA.mp47.37MB

5. Gradient Descent/14. Optimizers.mp49.18MB

5. Gradient Descent/15. Optimizers code along.mp410.69MB

5. Gradient Descent/16. Initialization code along.mp413.36MB

5. Gradient Descent/17. Inner Layers Visualization code along.mp432.28MB

5. Gradient Descent/18. Exercise 1 Presentation.mp43.52MB

5. Gradient Descent/19. Exercise 1 Solution.mp417.85MB

5. Gradient Descent/2. Derivatives and Gradient.mp410.47MB

5. Gradient Descent/20. Exercise 2 Presentation.mp42.44MB

5. Gradient Descent/21. Exercise 2 Solution.mp411.01MB

5. Gradient Descent/22. Exercise 3 Presentation.mp42.95MB

5. Gradient Descent/23. Exercise 3 Solution.mp412.56MB

5. Gradient Descent/24. Exercise 4 Presentation.mp43.69MB

5. Gradient Descent/25. Exercise 4 Solution.mp411.16MB

5. Gradient Descent/26. Tensorboard.mp48.29MB

5. Gradient Descent/3. Backpropagation intuition.mp47.21MB

5. Gradient Descent/4. Chain Rule.mp412.46MB

5. Gradient Descent/5. Derivative Calculation.mp47.2MB

5. Gradient Descent/6. Fully Connected Backpropagation.mp412.5MB

5. Gradient Descent/7. Matrix Notation.mp48.56MB

5. Gradient Descent/8. Numpy Arrays code along.mp419.43MB

5. Gradient Descent/9. Learning Rate.mp43.68MB

6. Convolutional Neural Networks/1. Section 6 Intro.mp435.44MB

6. Convolutional Neural Networks/10. Convolution in 2 D.mp46.67MB

6. Convolutional Neural Networks/11. Image Filters code along.mp46.41MB

6. Convolutional Neural Networks/12. Convolutional Layers.mp412.32MB

6. Convolutional Neural Networks/13. Convolutional Layers code along.mp414.41MB

6. Convolutional Neural Networks/14. Pooling Layers.mp43.06MB

6. Convolutional Neural Networks/15. Pooling Layers code along.mp45.27MB

6. Convolutional Neural Networks/16. Convolutional Neural Networks.mp44.51MB

6. Convolutional Neural Networks/17. Convolutional Neural Networks code along.mp413.97MB

6. Convolutional Neural Networks/18. Weights in CNNs.mp45.23MB

6. Convolutional Neural Networks/19. Beyond Images.mp45.27MB

6. Convolutional Neural Networks/2. Features from Pixels.mp47.96MB

6. Convolutional Neural Networks/20. Exercise 1 Presentation.mp417.26MB

6. Convolutional Neural Networks/21. Exercise 1 Solution.mp412.87MB

6. Convolutional Neural Networks/22. Exercise 2 Presentation.mp423.7MB

6. Convolutional Neural Networks/23. Exercise 2 Solution.mp410.72MB

6. Convolutional Neural Networks/3. MNIST Classification.mp43.94MB

6. Convolutional Neural Networks/4. MNIST Classification code along.mp419.63MB

6. Convolutional Neural Networks/5. Beyond Pixels.mp47.34MB

6. Convolutional Neural Networks/6. Images as Tensors.mp410.4MB

6. Convolutional Neural Networks/7. Tensor Math code along.mp417.19MB

6. Convolutional Neural Networks/8. Convolution in 1 D.mp46.63MB

6. Convolutional Neural Networks/9. Convolution in 1 D code along.mp45.14MB

8. Recurrent Neural Networks/1. Section 8 Intro.mp424.47MB

8. Recurrent Neural Networks/10. Exercise 1 Presentation.mp410.66MB

8. Recurrent Neural Networks/11. Exercise 1 Solution.mp47.95MB

8. Recurrent Neural Networks/12. Exercise 2 Presentation.mp48.22MB

8. Recurrent Neural Networks/2. Time Series.mp410.43MB

8. Recurrent Neural Networks/3. Sequence problems.mp48.76MB

8. Recurrent Neural Networks/4. Vanilla RNN.mp45.64MB

8. Recurrent Neural Networks/5. LSTM and GRU.mp411.47MB

8. Recurrent Neural Networks/6. Time Series Forecasting code along.mp416.13MB

8. Recurrent Neural Networks/7. Time Series Forecasting with LSTM code along.mp49.45MB

8. Recurrent Neural Networks/8. Rolling Windows.mp45.08MB

8. Recurrent Neural Networks/9. Rolling Windows code along.mp421.13MB

9. Improving performance/1. Section 9 Intro.mp419.19MB

9. Improving performance/10. Image Generator code along.mp415.32MB

9. Improving performance/11. Hyperparameter search.mp47.15MB

9. Improving performance/12. Embeddings.mp46.55MB

9. Improving performance/13. Embeddings code along.mp45.73MB

9. Improving performance/14. Movies Reviews Sentiment Analysis code along.mp426.73MB

9. Improving performance/15. Exercise 1 Presentation.mp47.64MB

9. Improving performance/17. Exercise 2 Presentation.mp45.5MB

9. Improving performance/19. Exercise 3 Presentation.mp423.87MB

9. Improving performance/2. Learning curves.mp45.46MB

9. Improving performance/3. Learning curves code along.mp418.94MB

9. Improving performance/4. Batch Normalization.mp43.83MB

9. Improving performance/5. Batch Normalization code along.mp415.01MB

9. Improving performance/6. Dropout.mp45.96MB

9. Improving performance/7. Dropout and Regularization code along.mp46.29MB

9. Improving performance/8. Data Augmentation.mp46.08MB

9. Improving performance/9. Continuous Learning.mp44.84MB