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[UdemyCourseDownloader] Deep Learning Recurrent Neural Networks in Python

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02/16/19 at 1:07pm GMT+1

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

Like the course I just released on Hidden Markov Models, Recurrent Neural Networks are all about learning sequences – but whereas Markov Models are limited by the Markov assumption, Recurrent Neural Networks are not – and as a result, they are more expressive, and more powerful than anything we’ve seen on tasks that we haven’t made progress on in decades.

So what’s going to be in this course and how will it build on the previous neural network courses and Hidden Markov Models?

In the first section of the course we are going to add the concept of time to our neural networks.

I’ll introduce you to the Simple Recurrent Unit, also known as the Elman unit.

We are going to revisit the XOR problem, but we’re going to extend it so that it becomes the parity problem – you’ll see that regular feedforward neural networks will have trouble solving this problem but recurrent networks will work because the key is to treat the input as a sequence.

In the next section of the course, we are going to revisit one of the most popular applications of recurrent neural networks – language modeling.

You saw when we studied Markov Models that we could do things like generate poetry and it didn’t look too bad. We could even discriminate between 2 different poets just from the sequence of parts-of-speech tags they used.

In this course, we are going to extend our language model so that it no longer makes the Markov assumption.

File list

[UdemyCourseDownloader] 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.vtt 4.3 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.vtt 4.6 KB
1. Introduction and Outline/3. Where to get the Code and Data.mp4 3.1 MB
1. Introduction and Outline/3. Where to get the Code and Data.vtt 2.3 KB
1. Introduction and Outline/4. How to Succeed in this Course.mp4 3.3 MB
1. Introduction and Outline/4. How to Succeed in this Course.vtt 3.7 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.vtt 6 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.vtt 6.8 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.vtt 2.4 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).vtt 5.5 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.vtt 5.6 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.vtt 10.3 KB
2. The Simple Recurrent Unit/7. Theano Scan Tutorial.mp4 23.8 MB
2. The Simple Recurrent Unit/7. Theano Scan Tutorial.vtt 11.3 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.vtt 10.9 KB
2. The Simple Recurrent Unit/9. On Adding Complexity.mp4 2.4 MB
2. The Simple Recurrent Unit/9. On Adding Complexity.vtt 1.6 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.vtt 6.7 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.vtt 3.2 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.vtt 3.9 KB
3. Recurrent Neural Networks for NLP/4. Generating Poetry.mp4 7.5 MB
3. Recurrent Neural Networks for NLP/4. Generating Poetry.vtt 5.4 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).vtt 13 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).vtt 2.9 KB
3. Recurrent Neural Networks for NLP/7. Classifying Poetry.mp4 6.3 MB
3. Recurrent Neural Networks for NLP/7. Classifying Poetry.vtt 4.3 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.vtt 11.1 KB
4. Advanced RNN Units/1. Rated RNN Unit.mp4 6.1 MB
4. Advanced RNN Units/1. Rated RNN Unit.vtt 4.6 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).vtt 5.6 KB
4. Advanced RNN Units/11. Visualizing the Word Embeddings.mp4 23.5 MB
4. Advanced RNN Units/11. Visualizing the Word Embeddings.vtt 8.9 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.vtt 5.6 KB
4. Advanced RNN Units/3. Gated Recurrent Unit (GRU).mp4 9 MB
4. Advanced RNN Units/3. Gated Recurrent Unit (GRU).vtt 6.5 KB
4. Advanced RNN Units/4. GRU in Code.mp4 15.1 MB
4. Advanced RNN Units/4. GRU in Code.vtt 3.7 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).vtt 5.1 KB
4. Advanced RNN Units/6. LSTM in Code.mp4 19.4 MB
4. Advanced RNN Units/6. LSTM in Code.vtt 5.3 KB
4. Advanced RNN Units/7. Learning from Wikipedia Data.mp4 12.8 MB
4. Advanced RNN Units/7. Learning from Wikipedia Data.vtt 8.6 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.vtt 7.8 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).vtt 13.4 KB
5. Batch Training/1. Batch Training for Simple RNN.mp4 16.6 MB
5. Batch Training/1. Batch Training for Simple RNN.vtt 12.4 KB
6. TensorFlow/1. Simple RNN in TensorFlow.mp4 12 MB
6. TensorFlow/1. Simple RNN in TensorFlow.vtt 10 KB
7. Basics Review/1. (Review) Theano Basics.mp4 93.5 MB
7. Basics Review/1. (Review) Theano Basics.vtt 6.8 KB
7. Basics Review/2. (Review) Theano Neural Network in Code.mp4 87 MB
7. Basics Review/2. (Review) Theano Neural Network in Code.vtt 3.7 KB
7. Basics Review/3. (Review) Tensorflow Basics.mp4 81.4 MB
7. Basics Review/3. (Review) Tensorflow Basics.vtt 5.6 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.vtt 5.2 KB
8. Appendix/1. What is the Appendix.mp4 5.5 MB
8. Appendix/1. What is the Appendix.vtt 3.4 KB
8. Appendix/10. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 4 MB
8. Appendix/10. BONUS Where to get Udemy coupons and FREE deep learning material.vtt 3.2 KB
8. Appendix/11. Python 2 vs Python 3.mp4 7.8 MB
8. Appendix/2. How to install wp2txt or WikiExtractor.py.mp4 3.8 MB
8. Appendix/2. How to install wp2txt or WikiExtractor.py.vtt 3.1 KB
8. Appendix/3. Windows-Focused Environment Setup 2018.mp4 186.4 MB
8. Appendix/3. Windows-Focused Environment Setup 2018.vtt 18.9 KB
8. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 43.9 MB
8. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 13.5 KB
8. Appendix/5. How to Code by Yourself (part 1).mp4 24.5 MB
8. Appendix/5. How to Code by Yourself (part 1).vtt 21.3 KB
8. Appendix/6. How to Code by Yourself (part 2).mp4 14.8 MB
8. Appendix/6. How to Code by Yourself (part 2).vtt 12.3 KB
8. Appendix/7. How to Succeed in this Course (Long Version).mp4 13 MB
8. Appendix/7. How to Succeed in this Course (Long Version).vtt 13.5 KB
8. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39 MB
8. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 29.8 KB
8. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp4 78.3 MB
8. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.vtt 13.2 KB
Udemy Course downloader.txt 94 B

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