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

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06/10/20 at 8:46pm GMT+1

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Description

Deep Learning: Recurrent Neural Networks in Python

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

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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]

File list

[FreeAllCourse.Com] Udemy - Deep Learning Recurrent Neural Networks in Python
1. Introduction and Outline/1. Outline of this Course.mp4 4.9 MB
1. Introduction and Outline/1. Outline of this Course.srt 4.8 KB
1. Introduction and Outline/2. Review of Important Deep Learning Concepts.mp4 5.7 MB
1. Introduction and Outline/2. Review of Important Deep Learning Concepts.srt 5.1 KB
1. Introduction and Outline/3. How to Succeed in this Course.mp4 3.3 MB
1. Introduction and Outline/3. How to Succeed in this Course.srt 7.5 KB
1. Introduction and Outline/4. Where to get the Code and Data.mp4 3.1 MB
1. Introduction and Outline/4. Where to get the Code and Data.srt 2.6 KB
1. Introduction and Outline/5. Preprocessed Wikipedia Data.mp4 21.6 MB
1. Introduction and Outline/5. Preprocessed Wikipedia Data.srt 4.1 KB
2. The Simple Recurrent Unit/1. Architecture of a Recurrent Unit.mp4 7.7 MB
2. The Simple Recurrent Unit/1. Architecture of a Recurrent Unit.srt 6.6 KB
2. The Simple Recurrent Unit/10. Suggestion Box.mp4 15.8 MB
2. The Simple Recurrent Unit/10. Suggestion Box.srt 4.8 KB
2. The Simple Recurrent Unit/2. Prediction and Relationship to Markov Models.mp4 9 MB
2. The Simple Recurrent Unit/2. Prediction and Relationship to Markov Models.srt 7.5 KB
2. The Simple Recurrent Unit/3. Unfolding a Recurrent Network.mp4 3.2 MB
2. The Simple Recurrent Unit/3. Unfolding a Recurrent Network.srt 2.6 KB
2. The Simple Recurrent Unit/4. Backpropagation Through Time (BPTT).mp4 7.1 MB
2. The Simple Recurrent Unit/4. Backpropagation Through Time (BPTT).srt 6.1 KB
2. The Simple Recurrent Unit/5. The Parity Problem - XOR on Steroids.mp4 7.8 MB
2. The Simple Recurrent Unit/5. The Parity Problem - XOR on Steroids.srt 6.2 KB
2. The Simple Recurrent Unit/6. The Parity Problem in Code using a Feedforward ANN.mp4 38.3 MB
2. The Simple Recurrent Unit/6. The Parity Problem in Code using a Feedforward ANN.srt 11.7 KB
2. The Simple Recurrent Unit/7. Theano Scan Tutorial.mp4 23.8 MB
2. The Simple Recurrent Unit/7. Theano Scan Tutorial.srt 12.7 KB
2. The Simple Recurrent Unit/8. The Parity Problem in Code using a Recurrent Neural Network.mp4 37.5 MB
2. The Simple Recurrent Unit/8. The Parity Problem in Code using a Recurrent Neural Network.srt 12.4 KB
2. The Simple Recurrent Unit/9. On Adding Complexity.mp4 2.4 MB
2. The Simple Recurrent Unit/9. On Adding Complexity.srt 1.8 KB
3. Recurrent Neural Networks for NLP/1. Word Embeddings and Recurrent Neural Networks.mp4 8.7 MB
3. Recurrent Neural Networks for NLP/1. Word Embeddings and Recurrent Neural Networks.srt 7.4 KB
3. Recurrent Neural Networks for NLP/2. Word Analogies with Word Embeddings.mp4 4.2 MB
3. Recurrent Neural Networks for NLP/2. Word Analogies with Word Embeddings.srt 3.6 KB
3. Recurrent Neural Networks for NLP/3. Representing a sequence of words as a sequence of word embeddings.mp4 5.4 MB
3. Recurrent Neural Networks for NLP/3. Representing a sequence of words as a sequence of word embeddings.srt 4.3 KB
3. Recurrent Neural Networks for NLP/4. Generating Poetry.mp4 7.5 MB
3. Recurrent Neural Networks for NLP/4. Generating Poetry.srt 5.9 KB
3. Recurrent Neural Networks for NLP/5. Generating Poetry in Code (part 1).mp4 52.4 MB
3. Recurrent Neural Networks for NLP/5. Generating Poetry in Code (part 1).srt 14.9 KB
3. Recurrent Neural Networks for NLP/6. Generating Poetry in Code (part 2).mp4 13.6 MB
3. Recurrent Neural Networks for NLP/6. Generating Poetry in Code (part 2).srt 3.2 KB
3. Recurrent Neural Networks for NLP/7. Classifying Poetry.mp4 6.3 MB
3. Recurrent Neural Networks for NLP/7. Classifying Poetry.srt 4.8 KB
3. Recurrent Neural Networks for NLP/8. Classifying Poetry in Code.mp4 45.9 MB
3. Recurrent Neural Networks for NLP/8. Classifying Poetry in Code.srt 12.5 KB
4. Advanced RNN Units/1. Rated RNN Unit.mp4 6 MB
4. Advanced RNN Units/1. Rated RNN Unit.srt 5.1 KB
4. Advanced RNN Units/10. Learning from Wikipedia Data in Code (part 2).mp4 25.6 MB
4. Advanced RNN Units/10. Learning from Wikipedia Data in Code (part 2).srt 6.3 KB
4. Advanced RNN Units/11. Visualizing the Word Embeddings.mp4 23.5 MB
4. Advanced RNN Units/11. Visualizing the Word Embeddings.srt 10.1 KB
4. Advanced RNN Units/2. RRNN in Code - Revisiting Poetry Generation.mp4 25.4 MB
4. Advanced RNN Units/2. RRNN in Code - Revisiting Poetry Generation.srt 6.4 KB
4. Advanced RNN Units/3. Gated Recurrent Unit (GRU).mp4 9 MB
4. Advanced RNN Units/3. Gated Recurrent Unit (GRU).srt 7.2 KB
4. Advanced RNN Units/4. GRU in Code.mp4 15.1 MB
4. Advanced RNN Units/4. GRU in Code.srt 4.2 KB
4. Advanced RNN Units/5. Long Short-Term Memory (LSTM).mp4 7.6 MB
4. Advanced RNN Units/5. Long Short-Term Memory (LSTM).srt 5.7 KB
4. Advanced RNN Units/6. LSTM in Code.mp4 19.4 MB
4. Advanced RNN Units/6. LSTM in Code.srt 6 KB
4. Advanced RNN Units/7. Learning from Wikipedia Data.mp4 12.7 MB
4. Advanced RNN Units/7. Learning from Wikipedia Data.srt 15.6 KB
4. Advanced RNN Units/8. Alternative to Wikipedia Data Brown Corpus.mp4 12.5 MB
4. Advanced RNN Units/8. Alternative to Wikipedia Data Brown Corpus.srt 14.5 KB
4. Advanced RNN Units/9. Learning from Wikipedia Data in Code (part 1).mp4 48.7 MB
4. Advanced RNN Units/9. Learning from Wikipedia Data in Code (part 1).srt 15.1 KB
5. Batch Training/1. Batch Training for Simple RNN.mp4 16.6 MB
5. Batch Training/1. Batch Training for Simple RNN.srt 23.4 KB
6. TensorFlow/1. Simple RNN in TensorFlow.mp4 12 MB
6. TensorFlow/1. Simple RNN in TensorFlow.srt 19 KB
7. Basics Review/1. (Review) Theano Basics.mp4 93.5 MB
7. Basics Review/1. (Review) Theano Basics.srt 13.3 KB
7. Basics Review/2. (Review) Theano Neural Network in Code.mp4 87 MB
7. Basics Review/2. (Review) Theano Neural Network in Code.srt 6.7 KB
7. Basics Review/3. (Review) Tensorflow Basics.mp4 81.4 MB
7. Basics Review/3. (Review) Tensorflow Basics.srt 10.2 KB
7. Basics Review/4. (Review) Tensorflow Neural Network in Code.mp4 97.3 MB
7. Basics Review/4. (Review) Tensorflow Neural Network in Code.srt 10 KB
8. Appendix FAQ/1. What is the Appendix.mp4 5.5 MB
8. Appendix FAQ/1. What is the Appendix.srt 6.3 KB
8. Appendix FAQ/2. How to install wp2txt or WikiExtractor.py.mp4 3.8 MB
8. Appendix FAQ/2. How to install wp2txt or WikiExtractor.py.srt 5.8 KB
8. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4 186.4 MB
8. Appendix FAQ/3. Windows-Focused Environment Setup 2018.srt 36.5 KB
8. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 43.9 MB
8. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 25.4 KB
8. Appendix FAQ/5. How to Code by Yourself (part 1).mp4 24.5 MB
8. Appendix FAQ/5. How to Code by Yourself (part 1).srt 40.6 KB
8. Appendix FAQ/6. How to Code by Yourself (part 2).mp4 14.8 MB
8. Appendix FAQ/6. How to Code by Yourself (part 2).srt 23.9 KB
8. Appendix FAQ/7. How to Succeed in this Course (Long Version).mp4 13 MB
8. Appendix FAQ/7. How to Succeed in this Course (Long Version).srt 25.9 KB
8. Appendix FAQ/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39 MB
8. Appendix FAQ/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 57.8 KB
Verify Files.txt 1 KB

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