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文档列表

11. Appendix FAQ/4. Windows-Focused Environment Setup 2018.mp4 195.4 MB
8. Recursive Neural Networks (Tree Neural Networks)/10. RNTN in Tensorflow (Code).mp4 139.9 MB
7. Using Neural Networks to Solve NLP Problems/5. Parts-of-Speech Tagging Recurrent Neural Network in Tensorflow.mp4 135.7 MB
4. Word Embeddings and Word2Vec/10. Word2Vec in Code with Numpy.mp4 113.5 MB
2. Beginner's Corner Working with Word Vectors/4. Pretrained word vectors from GloVe.mp4 102.2 MB
9. Theano and Tensorflow Basics Review/4. (Review) Tensorflow Neural Network in Code.mp4 102.1 MB
9. Theano and Tensorflow Basics Review/1. (Review) Theano Basics.mp4 98.0 MB
5. Word Embeddings using GloVe/2. Matrix Factorization for Recommender Systems - Basic Concepts.mp4 94.6 MB
9. Theano and Tensorflow Basics Review/2. (Review) Theano Neural Network in Code.mp4 91.3 MB
9. Theano and Tensorflow Basics Review/3. (Review) Tensorflow Basics.mp4 85.4 MB
11. Appendix FAQ/10. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
5. Word Embeddings using GloVe/11. GloVe in Tensorflow with Gradient Descent.mp4 78.5 MB
6. Unifying Word2Vec and GloVe/2. PMI in Code.mp4 76.7 MB
2. Beginner's Corner Working with Word Vectors/5. Pretrained word vectors from word2vec.mp4 66.3 MB
4. Word Embeddings and Word2Vec/5. Negative Sampling.mp4 62.1 MB
2. Beginner's Corner Working with Word Vectors/7. Text Classification in Code.mp4 57.2 MB
6. Unifying Word2Vec and GloVe/1. Pointwise Mutual Information - Word2Vec as Matrix Factorization.mp4 55.9 MB
8. Recursive Neural Networks (Tree Neural Networks)/7. Recursive Neural Network in Theano.mp4 55.1 MB
5. Word Embeddings using GloVe/14. Training GloVe with SVD (Singular Value Decomposition).mp4 54.5 MB
8. Recursive Neural Networks (Tree Neural Networks)/9. RNTN in Tensorflow (Tips).mp4 51.9 MB
7. Using Neural Networks to Solve NLP Problems/6. How does an HMM solve POS tagging.mp4 47.4 MB
4. Word Embeddings and Word2Vec/12. Word2Vec Tensorflow in Code.mp4 46.3 MB
5. Word Embeddings using GloVe/10. GloVe in Code - Theano Gradient Descent.mp4 46.2 MB
11. Appendix FAQ/5. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
5. Word Embeddings using GloVe/8. GloVe in Code - Numpy Gradient Descent.mp4 43.9 MB
5. Word Embeddings using GloVe/4. Expanding the Matrix Factorization Model.mp4 42.9 MB
7. Using Neural Networks to Solve NLP Problems/3. Parts-of-Speech Tagging Baseline.mp4 41.8 MB
3. Review of Language Modeling and Neural Networks/4. Neural Bigram Model.mp4 41.7 MB
11. Appendix FAQ/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
11. Appendix FAQ/11. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
11. Appendix FAQ/15. What order should I take your courses in (part 2).mp4 39.4 MB
8. Recursive Neural Networks (Tree Neural Networks)/1. Recursive Neural Networks Section Introduction.mp4 39.2 MB
1. Outline, Review, and Logistical Things/1. Introduction, Outline, and Review.mp4 38.9 MB
4. Word Embeddings and Word2Vec/2. CBOW.mp4 38.3 MB
2. Beginner's Corner Working with Word Vectors/1. What are vectors.mp4 37.1 MB
7. Using Neural Networks to Solve NLP Problems/4. Parts-of-Speech Tagging Recurrent Neural Network in Theano.mp4 36.5 MB
2. Beginner's Corner Working with Word Vectors/3. Trying to find and assess word vectors using TF-IDF and t-SNE.mp4 33.7 MB
4. Word Embeddings and Word2Vec/4. Hierarchical Softmax.mp4 32.8 MB
2. Beginner's Corner Working with Word Vectors/2. What is a word analogy.mp4 32.7 MB
4. Word Embeddings and Word2Vec/14. Word2Vec in Code with Theano.mp4 32.6 MB
11. Appendix FAQ/14. What order should I take your courses in (part 1).mp4 30.8 MB
5. Word Embeddings using GloVe/3. Matrix Factorization Training.mp4 30.2 MB
7. Using Neural Networks to Solve NLP Problems/12. Named Entity Recognition RNN in Tensorflow.mp4 29.9 MB
10. Legacy Word2vec Lectures/4. (Legacy) TF-IDF and t-SNE experiment.mp4 28.0 MB
11. Appendix FAQ/6. How to Code by Yourself (part 1).mp4 25.7 MB
8. Recursive Neural Networks (Tree Neural Networks)/2. Sentences as Trees.mp4 25.4 MB
5. Word Embeddings using GloVe/5. Regularization for Matrix Factorization.mp4 23.4 MB
1. Outline, Review, and Logistical Things/5. Preprocessed Wikipedia Data.mp4 22.6 MB
2. Beginner's Corner Working with Word Vectors/6. Text Classification with word vectors.mp4 21.6 MB
4. Word Embeddings and Word2Vec/6. Negative Sampling - Important Details.mp4 19.6 MB
1. Outline, Review, and Logistical Things/3. Tensorflow or Theano - Your Choice!.mp4 19.5 MB
10. Legacy Word2vec Lectures/1. (Legacy) What is a word embedding.mp4 18.9 MB
3. Review of Language Modeling and Neural Networks/3. Bigrams in Code.mp4 18.7 MB
11. Appendix FAQ/13. Is Theano Dead.mp4 18.7 MB
5. Word Embeddings using GloVe/1. GloVe Section Introduction.mp4 18.1 MB
7. Using Neural Networks to Solve NLP Problems/2. How can neural networks be used to solve POS tagging.mp4 17.7 MB
4. Word Embeddings and Word2Vec/3. Skip-Gram.mp4 16.9 MB
5. Word Embeddings using GloVe/7. Recap of ways to train GloVe.mp4 16.8 MB
4. Word Embeddings and Word2Vec/8. Word2Vec implementation tricks.mp4 16.4 MB
7. Using Neural Networks to Solve NLP Problems/10. Named Entity Recognition Baseline.mp4 15.6 MB
11. Appendix FAQ/7. How to Code by Yourself (part 2).mp4 15.5 MB
4. Word Embeddings and Word2Vec/9. Word2Vec implementation outline.mp4 15.2 MB
7. Using Neural Networks to Solve NLP Problems/7. Parts-of-Speech Tagging Hidden Markov Model (HMM).mp4 15.1 MB
7. Using Neural Networks to Solve NLP Problems/9. Comparing NER and POS tagging.mp4 15.0 MB
2. Beginner's Corner Working with Word Vectors/8. Using pretrained vectors later in the course.mp4 14.6 MB
11. Appendix FAQ/8. How to Succeed in this Course (Long Version).mp4 13.6 MB
11. Appendix FAQ/3. How to Uncompress a .tar.gz file.mp4 13.5 MB
4. Word Embeddings and Word2Vec/11. Word2Vec Tensorflow Implementation Details.mp4 13.5 MB
8. Recursive Neural Networks (Tree Neural Networks)/11. Recursive Neural Network in TensorFlow with Recursion.mp4 13.4 MB
4. Word Embeddings and Word2Vec/15. Alternative to Wikipedia Data Brown Corpus.mp4 13.1 MB
3. Review of Language Modeling and Neural Networks/2. Bigrams and Language Models.mp4 12.8 MB
3. Review of Language Modeling and Neural Networks/8. Improving Efficiency.mp4 12.5 MB
5. Word Embeddings using GloVe/9. GloVe in Code - Alternating Least Squares.mp4 12.2 MB
8. Recursive Neural Networks (Tree Neural Networks)/3. Data Description for Recursive Neural Networks.mp4 12.1 MB
4. Word Embeddings and Word2Vec/1. Return of the Bigram.mp4 12.1 MB
8. Recursive Neural Networks (Tree Neural Networks)/6. Trees to Sequences.mp4 11.7 MB
8. Recursive Neural Networks (Tree Neural Networks)/8. Recursive Neural Tensor Networks.mp4 11.6 MB
8. Recursive Neural Networks (Tree Neural Networks)/4. What are Recursive Neural Networks Tree Neural Networks (TNNs).mp4 10.0 MB
4. Word Embeddings and Word2Vec/13. How to update only part of a Theano shared variable.mp4 9.6 MB
5. Word Embeddings using GloVe/12. Visualizing country analogies with t-SNE.mp4 9.6 MB
10. Legacy Word2vec Lectures/5. (Legacy) Word2Vec introduction.mp4 9.3 MB
3. Review of Language Modeling and Neural Networks/5. Neural Bigram Model in Code.mp4 8.7 MB
8. Recursive Neural Networks (Tree Neural Networks)/5. Building a TNN with Recursion.mp4 8.5 MB
3. Review of Language Modeling and Neural Networks/6. Neural Network Bigram Model.mp4 8.4 MB
11. Appendix FAQ/12. Python 2 vs Python 3.mp4 8.2 MB
7. Using Neural Networks to Solve NLP Problems/1. Parts-of-Speech (POS) Tagging.mp4 8.1 MB
5. Word Embeddings using GloVe/6. GloVe - Global Vectors for Word Representation.mp4 7.4 MB
3. Review of Language Modeling and Neural Networks/9. Improving Efficiency in Code.mp4 7.1 MB
10. Legacy Word2vec Lectures/3. (Legacy) Word analogies using word embeddings.mp4 6.9 MB
1. Outline, Review, and Logistical Things/4. Where to get the code data for this course.mp4 6.8 MB
3. Review of Language Modeling and Neural Networks/1. Review Section Intro.mp4 5.8 MB
4. Word Embeddings and Word2Vec/7. Why do I have 2 word embedding matrices and what do I do with them.mp4 5.8 MB
11. Appendix FAQ/1. What is the Appendix.mp4 5.7 MB
7. Using Neural Networks to Solve NLP Problems/11. Named Entity Recognition RNN in Theano.mp4 5.7 MB
3. Review of Language Modeling and Neural Networks/7. Neural Network Bigram Model in Code.mp4 5.4 MB
7. Using Neural Networks to Solve NLP Problems/8. Named Entity Recognition (NER).mp4 5.2 MB
10. Legacy Word2vec Lectures/2. (Legacy) Using pre-trained word embeddings.mp4 4.3 MB
5. Word Embeddings using GloVe/13. Hyperparameter Challenge.mp4 4.2 MB
7. Using Neural Networks to Solve NLP Problems/13. Hyperparameter Challenge II.mp4 4.0 MB
11. Appendix FAQ/2. How to install wp2txt or WikiExtractor.py.mp4 4.0 MB
1. Outline, Review, and Logistical Things/2. How to Succeed in this Course.mp4 3.5 MB
3. Review of Language Modeling and Neural Networks/10. Review Section Summary.mp4 3.1 MB
11. Appendix FAQ/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 32.5 kB
5. Word Embeddings using GloVe/2. Matrix Factorization for Recommender Systems - Basic Concepts.srt 27.6 kB
11. Appendix FAQ/15. What order should I take your courses in (part 2).srt 23.6 kB
11. Appendix FAQ/6. How to Code by Yourself (part 1).srt 23.3 kB
11. Appendix FAQ/4. Windows-Focused Environment Setup 2018.srt 20.6 kB
4. Word Embeddings and Word2Vec/5. Negative Sampling.srt 18.5 kB
3. Review of Language Modeling and Neural Networks/8. Improving Efficiency.srt 18.0 kB
3. Review of Language Modeling and Neural Networks/3. Bigrams in Code.srt 17.8 kB
3. Review of Language Modeling and Neural Networks/2. Bigrams and Language Models.srt 17.7 kB
7. Using Neural Networks to Solve NLP Problems/5. Parts-of-Speech Tagging Recurrent Neural Network in Tensorflow.srt 16.6 kB
8. Recursive Neural Networks (Tree Neural Networks)/7. Recursive Neural Network in Theano.srt 16.5 kB
11. Appendix FAQ/14. What order should I take your courses in (part 1).srt 16.4 kB
8. Recursive Neural Networks (Tree Neural Networks)/9. RNTN in Tensorflow (Tips).srt 16.1 kB
6. Unifying Word2Vec and GloVe/1. Pointwise Mutual Information - Word2Vec as Matrix Factorization.srt 15.9 kB
11. Appendix FAQ/8. How to Succeed in this Course (Long Version).srt 15.0 kB
5. Word Embeddings using GloVe/8. GloVe in Code - Numpy Gradient Descent.srt 15.0 kB
11. Appendix FAQ/5. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14.8 kB
2. Beginner's Corner Working with Word Vectors/4. Pretrained word vectors from GloVe.srt 14.6 kB
11. Appendix FAQ/10. Proof that using Jupyter Notebook is the same as not using it.srt 14.5 kB
10. Legacy Word2vec Lectures/1. (Legacy) What is a word embedding.srt 14.1 kB
8. Recursive Neural Networks (Tree Neural Networks)/10. RNTN in Tensorflow (Code).srt 13.7 kB
11. Appendix FAQ/7. How to Code by Yourself (part 2).srt 13.6 kB
11. Appendix FAQ/13. Is Theano Dead.srt 13.2 kB
10. Legacy Word2vec Lectures/4. (Legacy) TF-IDF and t-SNE experiment.srt 13.2 kB
5. Word Embeddings using GloVe/14. Training GloVe with SVD (Singular Value Decomposition).srt 12.7 kB
7. Using Neural Networks to Solve NLP Problems/3. Parts-of-Speech Tagging Baseline.srt 12.5 kB
5. Word Embeddings using GloVe/4. Expanding the Matrix Factorization Model.srt 12.0 kB
4. Word Embeddings and Word2Vec/10. Word2Vec in Code with Numpy.srt 11.9 kB
3. Review of Language Modeling and Neural Networks/6. Neural Network Bigram Model.srt 11.6 kB
7. Using Neural Networks to Solve NLP Problems/6. How does an HMM solve POS tagging.srt 11.2 kB
4. Word Embeddings and Word2Vec/4. Hierarchical Softmax.srt 11.1 kB
2. Beginner's Corner Working with Word Vectors/1. What are vectors.srt 10.6 kB
2. Beginner's Corner Working with Word Vectors/2. What is a word analogy.srt 10.5 kB
4. Word Embeddings and Word2Vec/2. CBOW.srt 10.5 kB
5. Word Embeddings using GloVe/3. Matrix Factorization Training.srt 10.3 kB
8. Recursive Neural Networks (Tree Neural Networks)/3. Data Description for Recursive Neural Networks.srt 10.1 kB
3. Review of Language Modeling and Neural Networks/4. Neural Bigram Model.srt 9.9 kB
8. Recursive Neural Networks (Tree Neural Networks)/1. Recursive Neural Networks Section Introduction.srt 9.7 kB
7. Using Neural Networks to Solve NLP Problems/4. Parts-of-Speech Tagging Recurrent Neural Network in Theano.srt 9.4 kB
8. Recursive Neural Networks (Tree Neural Networks)/6. Trees to Sequences.srt 9.2 kB
1. Outline, Review, and Logistical Things/1. Introduction, Outline, and Review.srt 8.9 kB
8. Recursive Neural Networks (Tree Neural Networks)/8. Recursive Neural Tensor Networks.srt 8.7 kB
2. Beginner's Corner Working with Word Vectors/3. Trying to find and assess word vectors using TF-IDF and t-SNE.srt 8.6 kB
6. Unifying Word2Vec and GloVe/2. PMI in Code.srt 8.6 kB
2. Beginner's Corner Working with Word Vectors/5. Pretrained word vectors from word2vec.srt 8.3 kB
4. Word Embeddings and Word2Vec/15. Alternative to Wikipedia Data Brown Corpus.srt 8.2 kB
11. Appendix FAQ/11. BONUS Where to get Udemy coupons and FREE deep learning material.srt 8.1 kB
3. Review of Language Modeling and Neural Networks/5. Neural Bigram Model in Code.srt 8.1 kB
5. Word Embeddings using GloVe/11. GloVe in Tensorflow with Gradient Descent.srt 8.0 kB
8. Recursive Neural Networks (Tree Neural Networks)/4. What are Recursive Neural Networks Tree Neural Networks (TNNs).srt 8.0 kB
4. Word Embeddings and Word2Vec/13. How to update only part of a Theano shared variable.srt 7.9 kB
5. Word Embeddings using GloVe/5. Regularization for Matrix Factorization.srt 7.6 kB
2. Beginner's Corner Working with Word Vectors/7. Text Classification in Code.srt 7.5 kB
4. Word Embeddings and Word2Vec/14. Word2Vec in Code with Theano.srt 7.4 kB
9. Theano and Tensorflow Basics Review/1. (Review) Theano Basics.srt 7.4 kB
8. Recursive Neural Networks (Tree Neural Networks)/2. Sentences as Trees.srt 7.2 kB
10. Legacy Word2vec Lectures/5. (Legacy) Word2Vec introduction.srt 7.0 kB
7. Using Neural Networks to Solve NLP Problems/1. Parts-of-Speech (POS) Tagging.srt 6.9 kB
4. Word Embeddings and Word2Vec/6. Negative Sampling - Important Details.srt 6.8 kB
8. Recursive Neural Networks (Tree Neural Networks)/5. Building a TNN with Recursion.srt 6.8 kB
4. Word Embeddings and Word2Vec/8. Word2Vec implementation tricks.srt 6.3 kB
11. Appendix FAQ/12. Python 2 vs Python 3.srt 6.2 kB
9. Theano and Tensorflow Basics Review/3. (Review) Tensorflow Basics.srt 6.0 kB
3. Review of Language Modeling and Neural Networks/9. Improving Efficiency in Code.srt 5.8 kB
5. Word Embeddings using GloVe/6. GloVe - Global Vectors for Word Representation.srt 5.8 kB
4. Word Embeddings and Word2Vec/9. Word2Vec implementation outline.srt 5.7 kB
9. Theano and Tensorflow Basics Review/4. (Review) Tensorflow Neural Network in Code.srt 5.6 kB
7. Using Neural Networks to Solve NLP Problems/2. How can neural networks be used to solve POS tagging.srt 5.6 kB
2. Beginner's Corner Working with Word Vectors/6. Text Classification with word vectors.srt 5.6 kB
10. Legacy Word2vec Lectures/3. (Legacy) Word analogies using word embeddings.srt 5.6 kB
1. Outline, Review, and Logistical Things/3. Tensorflow or Theano - Your Choice!.srt 5.5 kB
8. Recursive Neural Networks (Tree Neural Networks)/11. Recursive Neural Network in TensorFlow with Recursion.srt 5.5 kB
7. Using Neural Networks to Solve NLP Problems/7. Parts-of-Speech Tagging Hidden Markov Model (HMM).srt 5.3 kB
4. Word Embeddings and Word2Vec/3. Skip-Gram.srt 5.3 kB
4. Word Embeddings and Word2Vec/11. Word2Vec Tensorflow Implementation Details.srt 5.1 kB
7. Using Neural Networks to Solve NLP Problems/10. Named Entity Recognition Baseline.srt 4.6 kB
2. Beginner's Corner Working with Word Vectors/8. Using pretrained vectors later in the course.srt 4.4 kB
3. Review of Language Modeling and Neural Networks/10. Review Section Summary.srt 4.4 kB
3. Review of Language Modeling and Neural Networks/1. Review Section Intro.srt 4.4 kB
7. Using Neural Networks to Solve NLP Problems/8. Named Entity Recognition (NER).srt 4.3 kB
11. Appendix FAQ/3. How to Uncompress a .tar.gz file.srt 4.2 kB
3. Review of Language Modeling and Neural Networks/7. Neural Network Bigram Model in Code.srt 4.1 kB
1. Outline, Review, and Logistical Things/2. How to Succeed in this Course.srt 4.1 kB
1. Outline, Review, and Logistical Things/5. Preprocessed Wikipedia Data.srt 3.9 kB
9. Theano and Tensorflow Basics Review/2. (Review) Theano Neural Network in Code.srt 3.9 kB
4. Word Embeddings and Word2Vec/1. Return of the Bigram.srt 3.9 kB
11. Appendix FAQ/1. What is the Appendix.srt 3.8 kB
5. Word Embeddings using GloVe/12. Visualizing country analogies with t-SNE.srt 3.7 kB
4. Word Embeddings and Word2Vec/12. Word2Vec Tensorflow in Code.srt 3.7 kB
11. Appendix FAQ/2. How to install wp2txt or WikiExtractor.py.srt 3.4 kB
5. Word Embeddings using GloVe/7. Recap of ways to train GloVe.srt 3.3 kB
5. Word Embeddings using GloVe/13. Hyperparameter Challenge.srt 3.3 kB
10. Legacy Word2vec Lectures/2. (Legacy) Using pre-trained word embeddings.srt 3.2 kB
7. Using Neural Networks to Solve NLP Problems/13. Hyperparameter Challenge II.srt 3.2 kB
5. Word Embeddings using GloVe/9. GloVe in Code - Alternating Least Squares.srt 3.1 kB
4. Word Embeddings and Word2Vec/7. Why do I have 2 word embedding matrices and what do I do with them.srt 3.0 kB
5. Word Embeddings using GloVe/1. GloVe Section Introduction.srt 3.0 kB
5. Word Embeddings using GloVe/10. GloVe in Code - Theano Gradient Descent.srt 2.8 kB
7. Using Neural Networks to Solve NLP Problems/9. Comparing NER and POS tagging.srt 2.7 kB
7. Using Neural Networks to Solve NLP Problems/12. Named Entity Recognition RNN in Tensorflow.srt 2.5 kB
1. Outline, Review, and Logistical Things/4. Where to get the code data for this course.srt 2.3 kB
7. Using Neural Networks to Solve NLP Problems/11. Named Entity Recognition RNN in Theano.srt 1.7 kB
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