[FTUForum.com] [UDEMY] Deep Learning Plunge into Deep Learning [FTU]番号下载_[FTUForum.com] [UDEMY] Deep Learning Plunge into Deep Learning [FTU]番号下载_[FTUForum.com] [UDEMY] Deep Learning Plunge into Deep Learning [FTU]下载

[FTUForum.com] [UDEMY] Deep Learning Plunge into Deep Learning [FTU]

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种子名称： [FTUForum.com] [UDEMY] Deep Learning Plunge into Deep Learning [FTU]
文件类型：视频
文件数目： 36个文件
文件大小： 1.08 GB
收录时间： 2021-5-6 18:20
已经下载： 3次
资源热度： 205
最近下载： 2024-12-20 10:41

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[FTUForum.com] [UDEMY] Deep Learning Plunge into Deep Learning [FTU].torrent

1. Introduction/1. Applications of Deep Learning.mp444.71MB

1. Introduction/2. What is Deep Learning.mp410.69MB

1. Introduction/3. Why Deep Learning.mp45.63MB

1. Introduction/4. Why now.mp416.47MB

2. Fundamentals/1. Hello World of Deep learning.mp45.72MB

2. Fundamentals/2. Dataset and Features.mp47.34MB

2. Fundamentals/3. Classification.mp410.13MB

3. Neural Networks/1. Perceptron.mp4102.93MB

3. Neural Networks/2. Sigmoid Function.mp443.02MB

3. Neural Networks/3. Softmax Function.mp455.92MB

3. Neural Networks/4. One Hot Encoding.mp430.71MB

3. Neural Networks/5. Activation Functions.mp424.89MB

3. Neural Networks/6. Logic Gates and XOR Problem.mp414.3MB

4. Training Neural Networks/1. Cross Entropy.mp436.99MB

4. Training Neural Networks/10. Drop out.mp47.92MB

4. Training Neural Networks/11. Vanishing Gradient Problem.mp423.84MB

4. Training Neural Networks/2. Loss Optimization.mp417.11MB

4. Training Neural Networks/3. Gradient Descent.mp467.55MB

4. Training Neural Networks/4. Non Linear Models.mp427.69MB

4. Training Neural Networks/5. Feed Forward.mp426.94MB

4. Training Neural Networks/6. Backward Propagation.mp413.6MB

4. Training Neural Networks/7. Overfitting problem.mp430.17MB

4. Training Neural Networks/8. Early Stopping.mp426.06MB

4. Training Neural Networks/9. Regularization.mp421.39MB

5. Convolution Neural Networks/1. Need for feature extraction.mp441.5MB

5. Convolution Neural Networks/2. Preprocessing.mp410.18MB

5. Convolution Neural Networks/3. Convolution Operation.mp4226.33MB

5. Convolution Neural Networks/4. Pooling Layer.mp429.92MB

5. Convolution Neural Networks/5. Flattening.mp415.11MB

6. Sequence Models/1. Recurrent Neural Networks.mp440.64MB

6. Sequence Models/2. LSTMs.mp418.65MB

6. Sequence Models/3. Architecture of LSTMs.mp420.03MB

6. Sequence Models/4. Forget Gate.mp416.91MB

6. Sequence Models/5. Learn Gate.mp49.62MB

6. Sequence Models/6. Remember Gate.mp42.41MB

6. Sequence Models/7. Use Gate.mp44.17MB