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

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[FreeAllCourse.Com] Udemy - Deep Learning Recurrent Neural Networks in Python 8. Appendix FAQ
  • 3. Windows-Focused Environment Setup 2018.mp4 (186.4 MB)
  • 1. What is the Appendix.mp4 (5.5 MB)
  • 1. What is the Appendix.srt (6.3 KB)
  • 2. How to install wp2txt or WikiExtractor.py.mp4 (3.8 MB)
  • 2. How to install wp2txt or WikiExtractor.py.srt (5.8 KB)
  • 3. Windows-Focused Environment Setup 2018.srt (36.5 KB)
  • 4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 (43.9 MB)
  • 4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt (25.4 KB)
  • 5. How to Code by Yourself (part 1).mp4 (24.5 MB)
  • 5. How to Code by Yourself (part 1).srt (40.6 KB)
  • 6. How to Code by Yourself (part 2).mp4 (14.8 MB)
  • 6. How to Code by Yourself (part 2).srt (23.9 KB)
  • 7. How to Succeed in this Course (Long Version).mp4 (13.0 MB)
  • 7. How to Succeed in this Course (Long Version).srt (25.9 KB)
  • 8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 (39.0 MB)
  • 8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt (57.8 KB)
  • 9. Proof that using Jupyter Notebook is the same as not using it.mp4 (78.3 MB)
  • 9. Proof that using Jupyter Notebook is the same as not using it.srt (25.2 KB)
  • 10. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 (37.8 MB)
  • 10. BONUS Where to get Udemy coupons and FREE deep learning material.srt (8.4 KB)
  • 11. Python 2 vs Python 3.mp4 (7.8 MB)
  • 11. Python 2 vs Python 3.srt (11.1 KB)
  • 12. Is Theano Dead.mp4 (17.8 MB)
  • 12. Is Theano Dead.srt (23.6 KB)
  • 13. What order should I take your courses in (part 1).mp4 (29.3 MB)
  • 13. What order should I take your courses in (part 1).srt (29.4 KB)
  • 14. What order should I take your courses in (part 2).mp4 (37.6 MB)
  • 14. What order should I take your courses in (part 2).srt (43.4 KB)
  • Verify Files.txt (1.0 KB)
    • 0. Websites you may like
    • [FreeAllCourse.Com].url (0.1 KB)
    1. Introduction and Outline
    • 1. Outline of this Course.mp4 (4.9 MB)
    • 1. Outline of this Course.srt (4.8 KB)
    • 2. Review of Important Deep Learning Concepts.mp4 (5.7 MB)
    • 2. Review of Important Deep Learning Concepts.srt (5.1 KB)
    • 3. How to Succeed in this Course.mp4 (3.3 MB)
    • 3. How to Succeed in this Course.srt (7.5 KB)
    • 4. Where to get the Code and Data.mp4 (3.1 MB)
    • 4. Where to get the Code and Data.srt (2.6 KB)
    • 5. Preprocessed Wikipedia Data.mp4 (21.6 MB)
    • 5. Preprocessed Wikipedia Data.srt (4.1 KB)
    2. The Simple Recurrent Unit
    • 1. Architecture of a Recurrent Unit.mp4 (7.7 MB)
    • 1. Architecture of a Recurrent Unit.srt (6.6 KB)
    • 2. Prediction and Relationship to Markov Models.mp4 (9.0 MB)
    • 2. Prediction and Relationship to Markov Models.srt (7.5 KB)
    • 3. Unfolding a Recurrent Network.mp4 (3.2 MB)
    • 3. Unfolding a Recurrent Network.srt (2.6 KB)
    • 4. Backpropagation Through Time (BPTT).mp4 (7.1 MB)
    • 4. Backpropagation Through Time (BPTT).srt (6.1 KB)
    • 5. The Parity Problem - XOR on Steroids.mp4 (7.8 MB)
    • 5. The Parity Problem - XOR on Steroids.srt (6.2 KB)
    • 6. The Parity Problem in Code using a Feedforward ANN.mp4 (38.3 MB)
    • 6. The Parity Problem in Code using a Feedforward ANN.srt (11.7 KB)
    • 7. Theano Scan Tutorial.mp4 (23.8 MB)
    • 7. Theano Scan Tutorial.srt (12.7 KB)
    • 8. The Parity Problem in Code using a Recurrent Neural Network.mp4 (37.5 MB)
    • 8. The Parity Problem in Code using a Recurrent Neural Network.srt (12.4 KB)
    • 9. On Adding Complexity.mp4 (2.4 MB)
    • 9. On Adding Complexity.srt (1.8 KB)
    • 10. Suggestion Box.mp4 (15.8 MB)
    • 10. Suggestion Box.srt (4.8 KB)
    3. Recurrent Neural Networks for NLP
    • 1. Word Embeddings and Recurrent Neural Networks.mp4 (8.7 MB)
    • 1. Word Embeddings and Recurrent Neural Networks.srt (7.4 KB)
    • 2. Word Analogies with Word Embeddings.mp4 (4.2 MB)
    • 2. Word Analogies with Word Embeddings.srt (3.6 KB)
    • 3. Representing a sequence of words as a sequence of word embeddings.mp4 (5.4 MB)
    • 3. Representing a sequence of words as a sequence of word embeddings.srt (4.3 KB)
    • 4. Generating Poetry.mp4 (7.5 MB)
    • 4. Generating Poetry.srt (5.9 KB)
    • 5. Generating Poetry in Code (part 1).mp4 (52.4 MB)
    • 5. Generating Poetry in Code (part 1).srt (14.9 KB)
    • 6. Generating Poetry in Code (part 2).mp4 (13.6 MB)
    • 6. Generating Poetry in Code (part 2).srt (3.2 KB)
    • 7. Classifying Poetry.mp4 (6.3 MB)
    • 7. Classifying Poetry.srt (4.8 KB)
    • 8. Classifying Poetry in Code.mp4 (45.9 MB)
    • 8. Classifying Poetry in Code.srt (12.5 KB)
    4. Advanced RNN Units
    • 1. Rated RNN Unit.mp4 (6.0 MB)
    • 1. Rated RNN Unit.srt (5.1 KB)
    • 2. RRNN in Code - Revisiting Poetry Generation.mp4 (25.4 MB)
    • 2. RRNN in Code - Revisiting Poetry Generation.srt (6.4 KB)
    • 3. Gated Recurrent Unit (GRU).mp4 (9.0 MB)
    • 3. Gated Recurrent Unit (GRU).srt (7.2 KB)
    • 4. GRU in Code.mp4 (15.1 MB)
    • 4. GRU in Code.srt (4.2 KB)
    • 5. Long Short-Term Memory (LSTM).mp4 (7.6 MB)
    • 5. Long Short-Term Memory (LSTM).srt (5.7 KB)
    • 6. LSTM in Code.mp4 (19.4 MB)
    • 6. LSTM in Code.srt (6.0 KB)
    • 7. Learning from Wikipedia Data.mp4 (12.7 MB)
    • 7. Learning from Wikipedia Data.srt (15.6 KB)
    • 8. Alternative to Wikipedia Data Brown Corpus.mp4 (12.5 MB)
    • 8. Alternative to Wikipedia Data Brown Corpus.srt (14.5 KB)
    • 9. Learning from Wikipedia Data in Code (part 1).mp4 (48.7 MB)
    • 9. Learning from Wikipedia Data in Code (part 1).srt (15.1 KB)
    • 10. Learning from Wikipedia Data in Code (part 2).mp4 (25.6 MB)
    • 10. Learning from Wikipedia Data in Code (part 2).srt (6.3 KB)
    • 11. Visualizing the Word Embeddings.mp4 (23.5 MB)
    • 11. Visualizing the Word Embeddings.srt (10.1 KB)
    5. Batch Training

    • Description

      Deep Learning: Recurrent Neural Networks in Python



      GRU, LSTM, + more modern deep learning, machine learning, and data science for sequences

      For More Paid Udemy Courses: FreeAllCourse.Com

      What you'll learn?

      # Understand the simple recurrent unit (Elman unit)
      # Understand the GRU (gated recurrent unit)
      # Understand the LSTM (long short-term memory unit)
      # Write various recurrent networks in Theano
      # Understand backpropagation through time
      # Understand how to mitigate the vanishing gradient problem
      # Solve the XOR and parity problems using a recurrent neural network
      # Use recurrent neural networks for language modeling
      # Use RNNs for generating text, like poetry
      # Visualize word embeddings and look for patterns in word vector representations

      Description

      Created by Lazy Programmer Inc.
      Last updated 12/2019
      Audio: English
      Caption: English [Auto-generated]




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

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

Torrent hash: 40AAD6F888B81AE8FA8BEFA1E18BD79BC562385F