Udemy - Natural Language Processing with Deep Learning in Python ...

Files:

• 1. Introduction, Outline, and Review.mp4 (37.1 MB)
• 1. Introduction, Outline, and Review.srt (8.7 KB)
• 2. How to Succeed in this Course.mp4 (3.3 MB)
• 2. How to Succeed in this Course.srt (4.0 KB)
• 3. Tensorflow or Theano - Your Choice!.mp4 (18.6 MB)
• 3. Tensorflow or Theano - Your Choice!.srt (5.4 KB)
• 4. Where to get the code data for this course.mp4 (6.5 MB)
• 4. Where to get the code data for this course.srt (2.2 KB)
• 5. Preprocessed Wikipedia Data.mp4 (21.6 MB)
• 5. Preprocessed Wikipedia Data.srt (3.8 KB)

• 1. (Legacy) What is a word embedding.mp4 (18.0 MB)
• 1. (Legacy) What is a word embedding.srt (13.8 KB)
• 2. (Legacy) Using pre-trained word embeddings.mp4 (4.1 MB)
• 2. (Legacy) Using pre-trained word embeddings.srt (3.1 KB)
• 3. (Legacy) Word analogies using word embeddings.mp4 (6.6 MB)
• 3. (Legacy) Word analogies using word embeddings.srt (5.5 KB)
• 4. (Legacy) TF-IDF and t-SNE experiment.mp4 (26.7 MB)
• 4. (Legacy) TF-IDF and t-SNE experiment.srt (12.9 KB)
• 5. (Legacy) Word2Vec introduction.mp4 (8.8 MB)
• 5. (Legacy) Word2Vec introduction.srt (6.8 KB)

• 1. What is the Appendix.mp4 (5.5 MB)
• 1. What is the Appendix.srt (3.7 KB)
• 10. Proof that using Jupyter Notebook is the same as not using it.mp4 (78.3 MB)
• 10. Proof that using Jupyter Notebook is the same as not using it.srt (14.1 KB)
• 11. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 (37.8 MB)
• 11. BONUS Where to get Udemy coupons and FREE deep learning material.srt (7.9 KB)
• 12. Python 2 vs Python 3.mp4 (7.8 MB)
• 12. Python 2 vs Python 3.srt (6.1 KB)
• 13. Is Theano Dead.mp4 (17.8 MB)
• 13. Is Theano Dead.srt (12.9 KB)
• 14. What order should I take your courses in (part 1).mp4 (29.3 MB)
• 14. What order should I take your courses in (part 1).srt (16.0 KB)
• 15. What order should I take your courses in (part 2).mp4 (37.6 MB)
• 15. What order should I take your courses in (part 2).srt (23.0 KB)
• 2. How to install wp2txt or WikiExtractor.py.mp4 (3.8 MB)
• 2. How to install wp2txt or WikiExtractor.py.srt (3.3 KB)
• 3. How to Uncompress a .tar.gz file.mp4 (12.9 MB)
• 3. How to Uncompress a .tar.gz file.srt (4.1 KB)
• 4. Windows-Focused Environment Setup 2018.mp4 (186.4 MB)
• 4. Windows-Focused Environment Setup 2018.srt (20.1 KB)
• 5. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 (43.9 MB)
• 5. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt (14.5 KB)
• 6. How to Code by Yourself (part 1).mp4 (24.5 MB)
• 6. How to Code by Yourself (part 1).srt (22.8 KB)
• 7. How to Code by Yourself (part 2).mp4 (14.8 MB)
• 7. How to Code by Yourself (part 2).srt (13.3 KB)
• 8. How to Succeed in this Course (Long Version).mp4 (13.0 MB)
• 8. How to Succeed in this Course (Long Version).srt (14.7 KB)
• 9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 (39.0 MB)
• 9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt (31.8 KB)

• 1. What are vectors.mp4 (35.3 MB)
• 1. What are vectors.srt (10.3 KB)
• 2. What is a word analogy.mp4 (31.2 MB)
• 2. What is a word analogy.srt (10.3 KB)
• 3. Trying to find and assess word vectors using TF-IDF and t-SNE.mp4 (32.1 MB)
• 3. Trying to find and assess word vectors using TF-IDF and t-SNE.srt (8.4 KB)
• 4. Pretrained word vectors from GloVe.mp4 (97.5 MB)
• 4. Pretrained word vectors from GloVe.srt (14.2 KB)
• 5. Pretrained word vectors from word2vec.mp4 (63.2 MB)
• 5. Pretrained word vectors from word2vec.srt (8.1 KB)
• 6. Text Classification with word vectors.mp4 (20.6 MB)
• 6. Text Classification with word vectors.srt (5.5 KB)
• 7. Text Classification in Code.mp4 (54.6 MB)
• 7. Text Classification in Code.srt (7.3 KB)
• 8. Using pretrained vectors later in the course.mp4 (13.9 MB)
• 8. Using pretrained vectors later in the course.srt (4.3 KB)

• 1. Review Section Intro.mp4 (5.5 MB)
• 1. Review Section Intro.srt (4.3 KB)
• 10. Review Section Summary.mp4 (3.0 MB)
• 10. Review Section Summary.srt (4.3 KB)
• 2. Bigrams and Language Models.mp4 (12.2 MB)
• 2. Bigrams and Language Models.srt (17.2 KB)
• 3. Bigrams in Code.mp4 (17.9 MB)
• 3. Bigrams in Code.srt (17.4 KB)
• 4. Neural Bigram Model.mp4 (39.7 MB)
• 4. Neural Bigram Model.srt (9.7 KB)
• 5. Neural Bigram Model in Code.mp4 (8.3 MB)
• 5. Neural Bigram Model in Code.srt (7.9 KB)
• 6. Neural Network Bigram Model.mp4 (8.0 MB)
• 6. Neural Network Bigram Model.srt (11.3 KB)
• 7. Neural Network Bigram Model in Code.mp4 (5.2 MB)
• 7. Neural Network Bigram Model in Code.srt (4.0 KB)
• 8. Improving Efficiency.mp4 (11.9 MB)
• 8. Improving Efficiency.srt (17.6 KB)
• 9. Improving Efficiency in Code.mp4 (6.7 MB)
• 9. Improving Efficiency in Code.srt (5.7 KB)

• 1. Return of the Bigram.mp4 (11.5 MB)
• 1. Return of the Bigram.srt (3.8 KB)
• 10. Word2Vec in Code with Numpy.mp4 (108.2 MB)
• 10. Word2Vec in Code with Numpy.srt (11.6 KB)
• 11. Word2Vec Tensorflow Implementation Details.mp4 (12.8 MB)
• 11. Word2Vec Tensorflow Implementation Details.srt (5.0 KB)
• 12. Word2Vec Tensorflow in Code.mp4 (44.2 MB)
• 12. Word2Vec Tensorflow in Code.srt (3.6 KB)
• 13. How to update only part of a Theano shared variable.mp4 (9.2 MB)
• 13. How to update only part of a Theano shared variable.srt (7.7 KB)
• 14. Word2Vec in Code with Theano.mp4 (31.0 MB)
• 14. Word2Vec in Code with Theano.srt (7.2 KB)
• 15. Alternative to Wikipedia Data Brown Corpus.mp4 (12.5 MB)
• 15. Alternative to Wikipedia Data Brown Corpus.srt (8.0 KB)
• 2. CBOW.mp4 (36.5 MB)
• 2. CBOW.srt (10.3 KB)
• 3. Skip-Gram.mp4 (16.1 MB)
• 3. Skip-Gram.srt (5.1 KB)
• 4. Hierarchical Softmax.mp4 (31.3 MB)
• 4. Hierarchical Softmax.srt (10.8 KB)
• 5. Negative Sampling.mp4 (59.2 MB)
• 5. Negative Sampling.srt (18.1 KB)
• 6. Negative Sampling - Important Details.mp4 (18.7 MB)
• 6. Negative Sampling - Important Details.srt (6.7 KB)
• 7. Why do I have 2 word embedding matrices and what do I do with them.mp4 (5.5 MB)
• 7. Why do I have 2 word embedding matrices and what do I do with them.srt (2.9 KB)
• 8. Word2Vec implementation tricks.mp4 (15.7 MB)
• 8. Word2Vec implementation tricks.srt (6.1 KB)
• 9. Word2Vec implementation outline.mp4 (14.5 MB)
• 9. Word2Vec implementation outline.srt (5.6 KB)

• 1. GloVe Section Introduction.mp4 (17.2 MB)
• 1. GloVe Section Introduction.srt (2.9 KB)
• 10. GloVe in Code - Theano Gradient Descent.mp4 (44.0 MB)
• 10. GloVe in Code - Theano Gradient Descent.srt (2.7 KB)
• 11. GloVe in Tensorflow with Gradient Descent.mp4 (74.9 MB)
• 11. GloVe in Tensorflow with Gradient Descent.srt (7.8 KB)
• 12. Visualizing country analogies with t-SNE.mp4 (9.2 MB)
• 12. Visualizing country analogies with t-SNE.srt (3.6 KB)
• 13. Hyperparameter Challenge.mp4 (4.1 MB)
• 13. Hyperparameter Challenge.srt (3.2 KB)
• 14. Training GloVe with SVD (Singular Value Decomposition).mp4 (52.0 MB)
• 14. Training GloVe with SVD (Singular Value Decomposition).srt (12.4 KB)
• 2. Matrix Factorization for Recommender Systems - Basic Concepts.mp4 (90.2 MB)
• 2. Matrix Factorization for Recommender Systems - Basic Concepts.srt (26.9 KB)
• 3. Matrix Factorization Training.mp4 (28.8 MB)
• 3. Matrix Factorization Training.srt (10.1 KB)
• 4. Expanding the Matrix Factorization Model.mp4 (40.9 MB)
• 4. Expanding the Matrix Factorization Model.srt (11.7 KB)
• 5. Regularization for Matrix Factorization.mp4 (22.3 MB)
• 5. Regularization for Matrix Factorization.srt (7.4 KB)
• 6. GloVe - Global Vectors for Word Representation.mp4 (7.1 MB)
• 6. GloVe - Global Vectors for Word Representation.srt (5.7 KB)
• 7. Recap of ways to train GloVe.mp4 (16.0 MB)
• 7. Recap of ways to train GloVe.srt (3.2 KB)
• 8. GloVe in Code - Numpy Gradient Descent.mp4 (41.9 MB)
• 8. GloVe in Code - Numpy Gradient Descent.srt (14.7 KB)
• 9. GloVe in Code - Alternating Least Squares.mp4 (11.6 MB)
• 9. GloVe in Code - Alternating Least Squares.srt (3.0 KB)

• 1. Pointwise Mutual Information - Word2Vec as Matrix Factorization.mp4 (53.3 MB)
• 1. Pointwise Mutual Information - Word2Vec as Matrix Factorization.srt (15.5 KB)
• 2. PMI in Code.mp4 (73.1 MB)
• 2. PMI in Code.srt (8.4 KB)

• 1. Parts-of-Speech (POS) Tagging.mp4 (7.8 MB)
• 1. Parts-of-Speech (POS) Tagging.srt (6.8 KB)
• 10. Named Entity Recognition Baseline.mp4 (14.9 MB)
• 10. Named Entity Recognition Baseline.srt (4.4 KB)
• 11. Named Entity Recognition RNN in Theano.mp4 (5.4 MB)
• 11. Named Entity Recognition RNN in Theano.srt (1.6 KB)
• 12. Named Entity Recognition RNN in Tensorflow.mp4 (28.5 MB)
• 12. Named Entity Recognition RNN in Tensorflow.srt (2.4 KB)
• 13. Hyperparameter Challenge II.mp4 (3.8 MB)
• 13. Hyperparameter Challenge II.srt (3.1 KB)
• 2. How can neural networks be used to solve POS tagging.mp4 (16.9 MB)
• 2. How can neural networks be used to solve POS tagging.srt (5.5 KB)
• 3. Parts-of-Speech Tagging Baseline.mp4 (39.9 MB)
• 3. Parts-of-Speech Tagging Baseline.srt (12.2 KB)
• 4. Parts-of-Speech Tagging Recurrent Neural Network in Theano.mp4 (34.8 MB)
• 4. Parts-of-Speech Tagging Recurrent Neural Network in Theano.srt (9.1 KB)
• 5. Parts-of-Speech Tagging Recurrent Neural Network in Tensorflow.mp4 (129.5 MB)
• 5. Parts-of-Speech Tagging Recurrent Neural Network in Tensorflow.srt (16.2 KB)
• 6. How does an HMM solve POS tagging.mp4 (45.2 MB)
• 6. How does an HMM solve POS tagging.srt (10.9 KB)
• 7. Parts-of-Speech Tagging Hidden Markov Model (HMM).mp4 (14.4 MB)
• 7. Parts-of-Speech Tagging Hidden Markov Model (HMM).srt (5.2 KB)
• 8. Named Entity Recognition (NER).mp4 (4.9 MB)
• 8. Named Entity Recognition (NER).srt (4.2 KB)
• 9. Comparing NER and POS tagging.mp4 (14.3 MB)
• 9. Comparing NER and POS tagging.srt (2.6 KB)

• 1. Recursive Neural Networks Section Introduction.mp4 (37.4 MB)
• 1. Recursive Neural Networks Section Introduction.srt (9.5 KB)
• 10. RNTN in Tensorflow (Code).mp4 (133.4 MB)
• 10. RNTN in Tensorflow (Code).srt (13.3 KB)
• 11. Recursive Neural Network in TensorFlow with Recursion.mp4 (12.8 MB)
• 11. Recursive Neural Network in TensorFlow with Recursion.srt (5.3 KB)
• 2. Sentences as Trees.mp4 (24.2 MB)
• 2. Sentences as Trees.srt (7.1 KB)
• 3. Data Description for Recursive Neural Networks.mp4 (11.5 MB)
• 3. Data Description for Recursive Neural Networks.srt (9.9 KB)
• 4. What are Recursive Neural Networks Tree Neural Networks (TNNs).mp4 (9.5 MB)
• 4. What are Recursive Neural Networks Tree Neural Networks (TNNs).srt (7.8 KB)
• 5. Building a TNN with Recursion.mp4 (8.1 MB)
• 5. Building a TNN with Recursion.srt (6.7 KB)
• 6. Trees to Sequences.mp4 (11.2 MB)
• 6. Trees to Sequences.srt (9.0 KB)
• 7. Recursive Neural Network in Theano.mp4 (52.5 MB)
• 7. Recursive Neural Network in Theano.srt (16.1 KB)
• 8. Recursive Neural Tensor Networks.mp4 (11.1 MB)
• 8. Recursive Neural Tensor Networks.srt (8.5 KB)
• 9. RNTN in Tensorflow (Tips).mp4 (49.5 MB)
• 9. RNTN in Tensorflow (Tips).srt (15.8 KB)

• 1. (Review) Theano Basics.mp4 (93.4 MB)
• 1. (Review) Theano Basics.srt (7.2 KB)
• 2. (Review) Theano Neural Network in Code.mp4 (87.0 MB)
• 2. (Review) Theano Neural Network in Code.srt (3.8 KB)
• 3. (Review) Tensorflow Basics.mp4 (81.4 MB)
• 3. (Review) Tensorflow Basics.srt (5.9 KB)
• 4. (Review) Tensorflow Neural Network in Code.mp4 (97.4 MB)
• 4. (Review) Tensorflow Neural Network in Code.srt (5.5 KB)

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