[FreeAllCourse.Com] Udemy - Deep Learning Recurrent Neural Networks in Python

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[FreeAllCourse.Com] Udemy - Deep Learning Recurrent Neural Networks in Python

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收录时间：2021-03-09
最近下载：2025-08-31

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文件列表

  • 8. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4 195.5 MB
  • 7. Basics Review/4. (Review) Tensorflow Neural Network in Code.mp4 102.1 MB
  • 7. Basics Review/1. (Review) Theano Basics.mp4 98.0 MB
  • 7. Basics Review/2. (Review) Theano Neural Network in Code.mp4 91.3 MB
  • 7. Basics Review/3. (Review) Tensorflow Basics.mp4 85.4 MB
  • 8. Appendix FAQ/9. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
  • 3. Recurrent Neural Networks for NLP/5. Generating Poetry in Code (part 1).mp4 55.0 MB
  • 4. Advanced RNN Units/9. Learning from Wikipedia Data in Code (part 1).mp4 51.1 MB
  • 3. Recurrent Neural Networks for NLP/8. Classifying Poetry in Code.mp4 48.1 MB
  • 8. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
  • 8. Appendix FAQ/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
  • 2. The Simple Recurrent Unit/6. The Parity Problem in Code using a Feedforward ANN.mp4 40.2 MB
  • 8. Appendix FAQ/10. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.6 MB
  • 8. Appendix FAQ/14. What order should I take your courses in (part 2).mp4 39.4 MB
  • 2. The Simple Recurrent Unit/8. The Parity Problem in Code using a Recurrent Neural Network.mp4 39.3 MB
  • 8. Appendix FAQ/13. What order should I take your courses in (part 1).mp4 30.8 MB
  • 4. Advanced RNN Units/10. Learning from Wikipedia Data in Code (part 2).mp4 26.9 MB
  • 4. Advanced RNN Units/2. RRNN in Code - Revisiting Poetry Generation.mp4 26.7 MB
  • 8. Appendix FAQ/5. How to Code by Yourself (part 1).mp4 25.7 MB
  • 2. The Simple Recurrent Unit/7. Theano Scan Tutorial.mp4 24.9 MB
  • 4. Advanced RNN Units/11. Visualizing the Word Embeddings.mp4 24.6 MB
  • 1. Introduction and Outline/5. Preprocessed Wikipedia Data.mp4 22.6 MB
  • 4. Advanced RNN Units/6. LSTM in Code.mp4 20.3 MB
  • 8. Appendix FAQ/12. Is Theano Dead.mp4 18.7 MB
  • 5. Batch Training/1. Batch Training for Simple RNN.mp4 17.4 MB
  • 2. The Simple Recurrent Unit/10. Suggestion Box.mp4 16.5 MB
  • 4. Advanced RNN Units/4. GRU in Code.mp4 15.8 MB
  • 8. Appendix FAQ/6. How to Code by Yourself (part 2).mp4 15.5 MB
  • 3. Recurrent Neural Networks for NLP/6. Generating Poetry in Code (part 2).mp4 14.3 MB
  • 8. Appendix FAQ/7. How to Succeed in this Course (Long Version).mp4 13.6 MB
  • 4. Advanced RNN Units/7. Learning from Wikipedia Data.mp4 13.4 MB
  • 4. Advanced RNN Units/8. Alternative to Wikipedia Data Brown Corpus.mp4 13.1 MB
  • 6. TensorFlow/1. Simple RNN in TensorFlow.mp4 12.6 MB
  • 4. Advanced RNN Units/3. Gated Recurrent Unit (GRU).mp4 9.5 MB
  • 2. The Simple Recurrent Unit/2. Prediction and Relationship to Markov Models.mp4 9.4 MB
  • 3. Recurrent Neural Networks for NLP/1. Word Embeddings and Recurrent Neural Networks.mp4 9.1 MB
  • 8. Appendix FAQ/11. Python 2 vs Python 3.mp4 8.2 MB
  • 2. The Simple Recurrent Unit/5. The Parity Problem - XOR on Steroids.mp4 8.2 MB
  • 2. The Simple Recurrent Unit/1. Architecture of a Recurrent Unit.mp4 8.1 MB
  • 4. Advanced RNN Units/5. Long Short-Term Memory (LSTM).mp4 8.0 MB
  • 3. Recurrent Neural Networks for NLP/4. Generating Poetry.mp4 7.9 MB
  • 2. The Simple Recurrent Unit/4. Backpropagation Through Time (BPTT).mp4 7.5 MB
  • 3. Recurrent Neural Networks for NLP/7. Classifying Poetry.mp4 6.6 MB
  • 4. Advanced RNN Units/1. Rated RNN Unit.mp4 6.3 MB
  • 1. Introduction and Outline/2. Review of Important Deep Learning Concepts.mp4 6.0 MB
  • 8. Appendix FAQ/1. What is the Appendix.mp4 5.7 MB
  • 3. Recurrent Neural Networks for NLP/3. Representing a sequence of words as a sequence of word embeddings.mp4 5.7 MB
  • 1. Introduction and Outline/1. Outline of this Course.mp4 5.2 MB
  • 3. Recurrent Neural Networks for NLP/2. Word Analogies with Word Embeddings.mp4 4.4 MB
  • 8. Appendix FAQ/2. How to install wp2txt or WikiExtractor.py.mp4 4.0 MB
  • 1. Introduction and Outline/3. How to Succeed in this Course.mp4 3.5 MB
  • 2. The Simple Recurrent Unit/3. Unfolding a Recurrent Network.mp4 3.4 MB
  • 1. Introduction and Outline/4. Where to get the Code and Data.mp4 3.3 MB
  • 2. The Simple Recurrent Unit/9. On Adding Complexity.mp4 2.5 MB
  • 8. Appendix FAQ/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 59.2 kB
  • 8. Appendix FAQ/14. What order should I take your courses in (part 2).srt 44.5 kB
  • 8. Appendix FAQ/5. How to Code by Yourself (part 1).srt 41.6 kB
  • 8. Appendix FAQ/3. Windows-Focused Environment Setup 2018.srt 37.3 kB
  • 8. Appendix FAQ/13. What order should I take your courses in (part 1).srt 30.1 kB
  • 8. Appendix FAQ/7. How to Succeed in this Course (Long Version).srt 26.5 kB
  • 8. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 26.0 kB
  • 8. Appendix FAQ/9. Proof that using Jupyter Notebook is the same as not using it.srt 25.8 kB
  • 8. Appendix FAQ/6. How to Code by Yourself (part 2).srt 24.5 kB
  • 8. Appendix FAQ/12. Is Theano Dead.srt 24.2 kB
  • 5. Batch Training/1. Batch Training for Simple RNN.srt 24.0 kB
  • 6. TensorFlow/1. Simple RNN in TensorFlow.srt 19.4 kB
  • 4. Advanced RNN Units/7. Learning from Wikipedia Data.srt 15.9 kB
  • 4. Advanced RNN Units/9. Learning from Wikipedia Data in Code (part 1).srt 15.5 kB
  • 3. Recurrent Neural Networks for NLP/5. Generating Poetry in Code (part 1).srt 15.2 kB
  • 4. Advanced RNN Units/8. Alternative to Wikipedia Data Brown Corpus.srt 14.9 kB
  • 7. Basics Review/1. (Review) Theano Basics.srt 13.6 kB
  • 2. The Simple Recurrent Unit/7. Theano Scan Tutorial.srt 13.1 kB
  • 3. Recurrent Neural Networks for NLP/8. Classifying Poetry in Code.srt 12.8 kB
  • 2. The Simple Recurrent Unit/8. The Parity Problem in Code using a Recurrent Neural Network.srt 12.7 kB
  • 2. The Simple Recurrent Unit/6. The Parity Problem in Code using a Feedforward ANN.srt 12.0 kB
  • 8. Appendix FAQ/11. Python 2 vs Python 3.srt 11.3 kB
  • 7. Basics Review/3. (Review) Tensorflow Basics.srt 10.5 kB
  • 4. Advanced RNN Units/11. Visualizing the Word Embeddings.srt 10.4 kB
  • 7. Basics Review/4. (Review) Tensorflow Neural Network in Code.srt 10.2 kB
  • 8. Appendix FAQ/10. BONUS Where to get Udemy coupons and FREE deep learning material.srt 8.6 kB
  • 2. The Simple Recurrent Unit/2. Prediction and Relationship to Markov Models.srt 7.7 kB
  • 1. Introduction and Outline/3. How to Succeed in this Course.srt 7.7 kB
  • 3. Recurrent Neural Networks for NLP/1. Word Embeddings and Recurrent Neural Networks.srt 7.6 kB
  • 4. Advanced RNN Units/3. Gated Recurrent Unit (GRU).srt 7.3 kB
  • 7. Basics Review/2. (Review) Theano Neural Network in Code.srt 6.9 kB
  • 2. The Simple Recurrent Unit/1. Architecture of a Recurrent Unit.srt 6.8 kB
  • 4. Advanced RNN Units/2. RRNN in Code - Revisiting Poetry Generation.srt 6.5 kB
  • 4. Advanced RNN Units/10. Learning from Wikipedia Data in Code (part 2).srt 6.5 kB
  • 8. Appendix FAQ/1. What is the Appendix.srt 6.5 kB
  • 2. The Simple Recurrent Unit/5. The Parity Problem - XOR on Steroids.srt 6.4 kB
  • 2. The Simple Recurrent Unit/4. Backpropagation Through Time (BPTT).srt 6.2 kB
  • 4. Advanced RNN Units/6. LSTM in Code.srt 6.2 kB
  • 3. Recurrent Neural Networks for NLP/4. Generating Poetry.srt 6.1 kB
  • 8. Appendix FAQ/2. How to install wp2txt or WikiExtractor.py.srt 5.9 kB
  • 4. Advanced RNN Units/5. Long Short-Term Memory (LSTM).srt 5.8 kB
  • 1. Introduction and Outline/2. Review of Important Deep Learning Concepts.srt 5.3 kB
  • 4. Advanced RNN Units/1. Rated RNN Unit.srt 5.2 kB
  • 2. The Simple Recurrent Unit/10. Suggestion Box.srt 4.9 kB
  • 1. Introduction and Outline/1. Outline of this Course.srt 4.9 kB
  • 3. Recurrent Neural Networks for NLP/7. Classifying Poetry.srt 4.9 kB
  • 3. Recurrent Neural Networks for NLP/3. Representing a sequence of words as a sequence of word embeddings.srt 4.4 kB
  • 4. Advanced RNN Units/4. GRU in Code.srt 4.3 kB
  • 1. Introduction and Outline/5. Preprocessed Wikipedia Data.srt 4.2 kB
  • 3. Recurrent Neural Networks for NLP/2. Word Analogies with Word Embeddings.srt 3.7 kB
  • 3. Recurrent Neural Networks for NLP/6. Generating Poetry in Code (part 2).srt 3.3 kB
  • 2. The Simple Recurrent Unit/3. Unfolding a Recurrent Network.srt 2.7 kB
  • 1. Introduction and Outline/4. Where to get the Code and Data.srt 2.6 kB
  • 2. The Simple Recurrent Unit/9. On Adding Complexity.srt 1.8 kB
  • Verify Files.txt 1.1 kB
  • 0. Websites you may like/[FreeAllCourse.Com].url 52 Bytes
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