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种子名称： [FreeCourseSite.com] Udemy - Deep Learning Recurrent Neural Networks in Python
文件类型： 视频
文件数目： 52个文件
文件大小： 1.36 GB
收录时间： 2019-2-11 03:31
已经下载： 3次
资源热度： 113
最近下载： 2024-8-13 10:46

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[FreeCourseSite.com] Udemy - Deep Learning Recurrent Neural Networks in Python.torrent

1. Introduction and Outline/1. Outline of this Course.mp44.93MB

1. Introduction and Outline/2. Review of Important Deep Learning Concepts.mp45.68MB

1. Introduction and Outline/3. Where to get the Code and Data.mp43.12MB

1. Introduction and Outline/4. How to Succeed in this Course.mp43.3MB

2. The Simple Recurrent Unit/1. Architecture of a Recurrent Unit.mp47.75MB

2. The Simple Recurrent Unit/2. Prediction and Relationship to Markov Models.mp48.97MB

2. The Simple Recurrent Unit/3. Unfolding a Recurrent Network.mp43.21MB

2. The Simple Recurrent Unit/4. Backpropagation Through Time (BPTT).mp47.15MB

2. The Simple Recurrent Unit/5. The Parity Problem - XOR on Steroids.mp47.79MB

2. The Simple Recurrent Unit/6. The Parity Problem in Code using a Feedforward ANN.mp438.33MB

2. The Simple Recurrent Unit/7. Theano Scan Tutorial.mp423.77MB

2. The Simple Recurrent Unit/8. The Parity Problem in Code using a Recurrent Neural Network.mp437.48MB

2. The Simple Recurrent Unit/9. On Adding Complexity.mp42.39MB

3. Recurrent Neural Networks for NLP/1. Word Embeddings and Recurrent Neural Networks.mp48.69MB

3. Recurrent Neural Networks for NLP/2. Word Analogies with Word Embeddings.mp44.18MB

3. Recurrent Neural Networks for NLP/3. Representing a sequence of words as a sequence of word embeddings.mp45.44MB

3. Recurrent Neural Networks for NLP/4. Generating Poetry.mp47.53MB

3. Recurrent Neural Networks for NLP/5. Generating Poetry in Code (part 1).mp452.43MB

3. Recurrent Neural Networks for NLP/6. Generating Poetry in Code (part 2).mp413.59MB

3. Recurrent Neural Networks for NLP/7. Classifying Poetry.mp46.28MB

3. Recurrent Neural Networks for NLP/8. Classifying Poetry in Code.mp445.87MB

4. Advanced RNN Units/1. Rated RNN Unit.mp46.05MB

4. Advanced RNN Units/10. Learning from Wikipedia Data in Code (part 2).mp425.61MB

4. Advanced RNN Units/11. Visualizing the Word Embeddings.mp423.49MB

4. Advanced RNN Units/2. RRNN in Code - Revisiting Poetry Generation.mp425.41MB

4. Advanced RNN Units/3. Gated Recurrent Unit (GRU).mp49.03MB

4. Advanced RNN Units/4. GRU in Code.mp415.07MB

4. Advanced RNN Units/5. Long Short-Term Memory (LSTM).mp47.62MB

4. Advanced RNN Units/6. LSTM in Code.mp419.39MB

4. Advanced RNN Units/7. Learning from Wikipedia Data.mp412.76MB

4. Advanced RNN Units/8. Alternative to Wikipedia Data Brown Corpus.mp412.49MB

4. Advanced RNN Units/9. Learning from Wikipedia Data in Code (part 1).mp448.69MB

5. Batch Training/1. Batch Training for Simple RNN.mp416.56MB

6. TensorFlow/1. Simple RNN in TensorFlow.mp412MB

7. Basics Review/1. (Review) Theano Basics.mp493.47MB

7. Basics Review/2. (Review) Theano Neural Network in Code.mp487.03MB

7. Basics Review/3. (Review) Tensorflow Basics.mp481.44MB

7. Basics Review/4. (Review) Tensorflow Neural Network in Code.mp497.34MB

8. Appendix/1. What is the Appendix.mp45.45MB

8. Appendix/10. BONUS Where to get Udemy coupons and FREE deep learning material.mp44.02MB

8. Appendix/11. Python 2 vs Python 3.mp47.83MB

8. Appendix/12. Is Theano Dead.mp417.82MB

8. Appendix/13. What order should I take your courses in (part 1).mp429.33MB

8. Appendix/14. What order should I take your courses in (part 2).mp437.62MB

8. Appendix/2. How to install wp2txt or WikiExtractor.py.mp43.77MB

8. Appendix/3. Windows-Focused Environment Setup 2018.mp4186.44MB

8. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp443.92MB

8. Appendix/5. How to Code by Yourself (part 1).mp424.53MB

8. Appendix/6. How to Code by Yourself (part 2).mp414.81MB

8. Appendix/7. How to Succeed in this Course (Long Version).mp412.99MB

8. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp438.95MB

8. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp478.31MB