| 1. (Legacy) What is a word embedding.mp4 | 18 MB | ||
| 1. (Legacy) What is a word embedding.srt | 13.8 KB | ||
| 1. (Review) Theano Basics.mp4 | 93.4 MB | ||
| 1. (Review) Theano Basics.srt | 7.2 KB | ||
| 1. GloVe Section Introduction.mp4 | 17.2 MB | ||
| 1. GloVe Section Introduction.srt | 2.9 KB | ||
| 1. Introduction, Outline, and Review.mp4 | 37.1 MB | ||
| 1. Introduction, Outline, and Review.srt | 8.7 KB | ||
| 1. Parts-of-Speech (POS) Tagging.mp4 | 7.8 MB | ||
| 1. Parts-of-Speech (POS) Tagging.srt | 6.8 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 | ||
| 1. Recursive Neural Networks Section Introduction.mp4 | 37.4 MB | ||
| 1. Recursive Neural Networks Section Introduction.srt | 9.5 KB | ||
| 1. Return of the Bigram.mp4 | 11.5 MB | ||
| 1. Return of the Bigram.srt | 3.8 KB | ||
| 1. Review Section Intro.mp4 | 5.5 MB | ||
| 1. Review Section Intro.srt | 4.3 KB | ||
| 1. What are vectors.mp4 | 35.3 MB | ||
| 1. What are vectors.srt | 10.3 KB | ||
| 1. What is the Appendix.mp4 | 5.5 MB | ||
| 1. What is the Appendix.srt | 3.7 KB | ||
| 10. GloVe in Code - Theano Gradient Descent.mp4 | 44 MB | ||
| 10. GloVe in Code - Theano Gradient Descent.srt | 2.7 KB | ||
| 10. Named Entity Recognition Baseline.mp4 | 14.9 MB | ||
| 10. Named Entity Recognition Baseline.srt | 4.4 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 | ||
| 10. RNTN in Tensorflow (Code).mp4 | 133.4 MB | ||
| 10. RNTN in Tensorflow (Code).srt | 13.3 KB | ||
| 10. Review Section Summary.mp4 | 3 MB | ||
| 10. Review Section Summary.srt | 4.3 KB | ||
| 10. Word2Vec in Code with Numpy.mp4 | 108.2 MB | ||
| 10. Word2Vec in Code with Numpy.srt | 11.6 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 | ||
| 11. GloVe in Tensorflow with Gradient Descent.mp4 | 74.9 MB | ||
| 11. GloVe in Tensorflow with Gradient Descent.srt | 7.8 KB | ||
| 11. Named Entity Recognition RNN in Theano.mp4 | 5.4 MB | ||
| 11. Named Entity Recognition RNN in Theano.srt | 1.6 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 | ||
| 11. Word2Vec Tensorflow Implementation Details.mp4 | 12.8 MB | ||
| 11. Word2Vec Tensorflow Implementation Details.srt | 5 KB | ||
| 12. Named Entity Recognition RNN in Tensorflow.mp4 | 28.5 MB | ||
| 12. Named Entity Recognition RNN in Tensorflow.srt | 2.4 KB | ||
| 12. Python 2 vs Python 3.mp4 | 7.8 MB | ||
| 12. Python 2 vs Python 3.srt | 6.1 KB | ||
| 12. Visualizing country analogies with t-SNE.mp4 | 9.2 MB | ||
| 12. Visualizing country analogies with t-SNE.srt | 3.6 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 | ||
| 13. Hyperparameter Challenge II.mp4 | 3.8 MB | ||
| 13. Hyperparameter Challenge II.srt | 3.1 KB | ||
| 13. Hyperparameter Challenge.mp4 | 4.1 MB | ||
| 13. Hyperparameter Challenge.srt | 3.2 KB | ||
| 13. Is Theano Dead.mp4 | 17.8 MB | ||
| 13. Is Theano Dead.srt | 12.9 KB | ||
| 14. Training GloVe with SVD (Singular Value Decomposition).mp4 | 52 MB | ||
| 14. Training GloVe with SVD (Singular Value Decomposition).srt | 12.4 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 KB | ||
| 14. Word2Vec in Code with Theano.mp4 | 31 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 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 KB | ||
| 2. (Legacy) Using pre-trained word embeddings.mp4 | 4.1 MB | ||
| 2. (Legacy) Using pre-trained word embeddings.srt | 3.1 KB | ||
| 2. (Review) Theano Neural Network in Code.mp4 | 87 MB | ||
| 2. (Review) Theano Neural Network in Code.srt | 3.8 KB | ||
| 2. Bigrams and Language Models.mp4 | 12.2 MB | ||
| 2. Bigrams and Language Models.srt | 17.2 KB | ||
| 2. CBOW.mp4 | 36.5 MB | ||
| 2. CBOW.srt | 10.3 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 | ||
| 2. How to Succeed in this Course.mp4 | 3.3 MB | ||
| 2. How to Succeed in this Course.srt | 4 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 | ||
| 2. Matrix Factorization for Recommender Systems - Basic Concepts.mp4 | 90.2 MB | ||
| 2. Matrix Factorization for Recommender Systems - Basic Concepts.srt | 26.9 KB | ||
| 2. PMI in Code.mp4 | 73.1 MB | ||
| 2. PMI in Code.srt | 8.4 KB | ||
| 2. Sentences as Trees.mp4 | 24.2 MB | ||
| 2. Sentences as Trees.srt | 7.1 KB | ||
| 2. What is a word analogy.mp4 | 31.2 MB | ||
| 2. What is a word analogy.srt | 10.3 KB | ||
| 3. (Legacy) Word analogies using word embeddings.mp4 | 6.6 MB | ||
| 3. (Legacy) Word analogies using word embeddings.srt | 5.5 KB | ||
| 3. (Review) Tensorflow Basics.mp4 | 81.4 MB | ||
| 3. (Review) Tensorflow Basics.srt | 5.9 KB | ||
| 3. Bigrams in Code.mp4 | 17.9 MB | ||
| 3. Bigrams in Code.srt | 17.4 KB | ||
| 3. Data Description for Recursive Neural Networks.mp4 | 11.5 MB | ||
| 3. Data Description for Recursive Neural Networks.srt | 9.9 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 | ||
| 3. Matrix Factorization Training.mp4 | 28.8 MB | ||
| 3. Matrix Factorization Training.srt | 10.1 KB | ||
| 3. Parts-of-Speech Tagging Baseline.mp4 | 39.9 MB | ||
| 3. Parts-of-Speech Tagging Baseline.srt | 12.2 KB | ||
| 3. Skip-Gram.mp4 | 16.1 MB | ||
| 3. Skip-Gram.srt | 5.1 KB | ||
| 3. Tensorflow or Theano - Your Choice!.mp4 | 18.6 MB | ||
| 3. Tensorflow or Theano - Your Choice!.srt | 5.4 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. (Legacy) TF-IDF and t-SNE experiment.mp4 | 26.7 MB | ||
| 4. (Legacy) TF-IDF and t-SNE experiment.srt | 12.9 KB | ||
| 4. (Review) Tensorflow Neural Network in Code.mp4 | 97.4 MB | ||
| 4. (Review) Tensorflow Neural Network in Code.srt | 5.5 KB | ||
| 4. Expanding the Matrix Factorization Model.mp4 | 40.9 MB | ||
| 4. Expanding the Matrix Factorization Model.srt | 11.7 KB | ||
| 4. Hierarchical Softmax.mp4 | 31.3 MB | ||
| 4. Hierarchical Softmax.srt | 10.8 KB | ||
| 4. Neural Bigram Model.mp4 | 39.7 MB | ||
| 4. Neural Bigram Model.srt | 9.7 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 | ||
| 4. Pretrained word vectors from GloVe.mp4 | 97.5 MB | ||
| 4. Pretrained word vectors from GloVe.srt | 14.2 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 | ||
| 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 | ||
| 4. Windows-Focused Environment Setup 2018.mp4 | 186.4 MB | ||
| 4. Windows-Focused Environment Setup 2018.srt | 20.1 KB | ||
| 5. (Legacy) Word2Vec introduction.mp4 | 8.8 MB | ||
| 5. (Legacy) Word2Vec introduction.srt | 6.8 KB | ||
| 5. Building a TNN with Recursion.mp4 | 8.1 MB | ||
| 5. Building a TNN with Recursion.srt | 6.7 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 | ||
| 5. Negative Sampling.mp4 | 59.2 MB | ||
| 5. Negative Sampling.srt | 18.1 KB | ||
| 5. Neural Bigram Model in Code.mp4 | 8.3 MB | ||
| 5. Neural Bigram Model in Code.srt | 7.9 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 | ||
| 5. Preprocessed Wikipedia Data.mp4 | 21.6 MB | ||
| 5. Preprocessed Wikipedia Data.srt | 3.8 KB | ||
| 5. Pretrained word vectors from word2vec.mp4 | 63.2 MB | ||
| 5. Pretrained word vectors from word2vec.srt | 8.1 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 | ||
| 6. How does an HMM solve POS tagging.mp4 | 45.2 MB | ||
| 6. How does an HMM solve POS tagging.srt | 10.9 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 | ||
| 6. Negative Sampling - Important Details.mp4 | 18.7 MB | ||
| 6. Negative Sampling - Important Details.srt | 6.7 KB | ||
| 6. Neural Network Bigram Model.mp4 | 8 MB | ||
| 6. Neural Network Bigram Model.srt | 11.3 KB | ||
| 6. Text Classification with word vectors.mp4 | 20.6 MB | ||
| 6. Text Classification with word vectors.srt | 5.5 KB | ||
| 6. Trees to Sequences.mp4 | 11.2 MB | ||
| 6. Trees to Sequences.srt | 9 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 | ||
| 7. Neural Network Bigram Model in Code.mp4 | 5.2 MB | ||
| 7. Neural Network Bigram Model in Code.srt | 4 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 | ||
| 7. Recap of ways to train GloVe.mp4 | 16 MB | ||
| 7. Recap of ways to train GloVe.srt | 3.2 KB | ||
| 7. Recursive Neural Network in Theano.mp4 | 52.5 MB | ||
| 7. Recursive Neural Network in Theano.srt | 16.1 KB | ||
| 7. Text Classification in Code.mp4 | 54.6 MB | ||
| 7. Text Classification in Code.srt | 7.3 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. GloVe in Code - Numpy Gradient Descent.mp4 | 41.9 MB | ||
| 8. GloVe in Code - Numpy Gradient Descent.srt | 14.7 KB | ||
| 8. How to Succeed in this Course (Long Version).mp4 | 13 MB | ||
| 8. How to Succeed in this Course (Long Version).srt | 14.7 KB | ||
| 8. Improving Efficiency.mp4 | 11.9 MB | ||
| 8. Improving Efficiency.srt | 17.6 KB | ||
| 8. Named Entity Recognition (NER).mp4 | 4.9 MB | ||
| 8. Named Entity Recognition (NER).srt | 4.2 KB | ||
| 8. Recursive Neural Tensor Networks.mp4 | 11.1 MB | ||
| 8. Recursive Neural Tensor Networks.srt | 8.5 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 | ||
| 8. Word2Vec implementation tricks.mp4 | 15.7 MB | ||
| 8. Word2Vec implementation tricks.srt | 6.1 KB | ||
| 9. Comparing NER and POS tagging.mp4 | 14.3 MB | ||
| 9. Comparing NER and POS tagging.srt | 2.6 KB | ||
| 9. GloVe in Code - Alternating Least Squares.mp4 | 11.6 MB | ||
| 9. GloVe in Code - Alternating Least Squares.srt | 3 KB | ||
| 9. Improving Efficiency in Code.mp4 | 6.7 MB | ||
| 9. Improving Efficiency in Code.srt | 5.7 KB | ||
| 9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 | 39 MB | ||
| 9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt | 31.8 KB | ||
| 9. RNTN in Tensorflow (Tips).mp4 | 49.5 MB | ||
| 9. RNTN in Tensorflow (Tips).srt | 15.8 KB | ||
| 9. Word2Vec implementation outline.mp4 | 14.5 MB | ||
| 9. Word2Vec implementation outline.srt | 5.6 KB | ||
| [CourseClub.Me].url | 0 B | ||
| [DesireCourse.Net].url | 0 B | ||
| [FreeCourseWorld.Com].url | 102 B | ||
| ▲ 207 total files | |||
Natural Language Processing with Deep Learning in Python
Complete guide on deriving and implementing word2vec, GLoVe, word embeddings, and sentiment analysis with recursive nets
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