Udemy - Natural Language Processing with Deep Learning in Python (12.2019)

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Udemy - Natural Language Processing with Deep Learning in Python (12.2019)

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收录时间：2025-09-01
最近下载：2025-09-01

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文件列表

  • 11. Appendix/3. 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 94.5 MB
  • 9. Theano and Tensorflow Basics Review/2. (Review) Theano Neural Network in Code.mp4 91.2 MB
  • 9. Theano and Tensorflow Basics Review/3. (Review) Tensorflow Basics.mp4 85.4 MB
  • 11. Appendix/9. 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 62.0 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/4. 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/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
  • 11. Appendix/14. 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/13. What order should I take your courses in (part 1).mp4 30.7 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/5. 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
  • 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/4. 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/12. 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 16.8 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/6. 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/7. How to Succeed in this Course (Long Version).mp4 13.6 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 9.2 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/11. 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/2. 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/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
  • 11. Appendix/10. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 4.2 MB
  • 7. Using Neural Networks to Solve NLP Problems/13. Hyperparameter Challenge II.mp4 4.0 MB
  • 11. Appendix/2. How to install wp2txt or WikiExtractor.py.mp4 4.0 MB
  • 1. Outline, Review, and Logistical Things/3. 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/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 28.4 kB
  • 5. Word Embeddings using GloVe/2. Matrix Factorization for Recommender Systems - Basic Concepts.vtt 24.0 kB
  • 11. Appendix/14. What order should I take your courses in (part 2).vtt 20.7 kB
  • 11. Appendix/5. How to Code by Yourself (part 1).vtt 20.3 kB
  • 11. Appendix/3. Windows-Focused Environment Setup 2018.vtt 17.8 kB
  • 4. Word Embeddings and Word2Vec/5. Negative Sampling.vtt 16.1 kB
  • 3. Review of Language Modeling and Neural Networks/8. Improving Efficiency.vtt 15.7 kB
  • 3. Review of Language Modeling and Neural Networks/3. Bigrams in Code.vtt 15.5 kB
  • 3. Review of Language Modeling and Neural Networks/2. Bigrams and Language Models.vtt 15.4 kB
  • 7. Using Neural Networks to Solve NLP Problems/5. Parts-of-Speech Tagging Recurrent Neural Network in Tensorflow.vtt 14.5 kB
  • 8. Recursive Neural Networks (Tree Neural Networks)/7. Recursive Neural Network in Theano.vtt 14.4 kB
  • 11. Appendix/13. What order should I take your courses in (part 1).vtt 14.4 kB
  • 8. Recursive Neural Networks (Tree Neural Networks)/9. RNTN in Tensorflow (Tips).vtt 14.2 kB
  • 6. Unifying Word2Vec and GloVe/1. Pointwise Mutual Information - Word2Vec as Matrix Factorization.vtt 14.0 kB
  • 5. Word Embeddings using GloVe/8. GloVe in Code - Numpy Gradient Descent.vtt 13.2 kB
  • 11. Appendix/7. How to Succeed in this Course (Long Version).vtt 13.2 kB
  • 10. Legacy Word2vec Lectures/1. (Legacy) What is a word embedding.vtt 12.7 kB
  • 11. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 12.7 kB
  • 2. Beginner's Corner Working with Word Vectors/4. Pretrained word vectors from GloVe.vtt 12.6 kB
  • 11. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.vtt 12.5 kB
  • 8. Recursive Neural Networks (Tree Neural Networks)/10. RNTN in Tensorflow (Code).vtt 11.9 kB
  • 11. Appendix/6. How to Code by Yourself (part 2).vtt 11.9 kB
  • 10. Legacy Word2vec Lectures/4. (Legacy) TF-IDF and t-SNE experiment.vtt 11.8 kB
  • 11. Appendix/12. Is Theano Dead.vtt 11.6 kB
  • 5. Word Embeddings using GloVe/14. Training GloVe with SVD (Singular Value Decomposition).vtt 11.2 kB
  • 7. Using Neural Networks to Solve NLP Problems/3. Parts-of-Speech Tagging Baseline.vtt 11.0 kB
  • 5. Word Embeddings using GloVe/4. Expanding the Matrix Factorization Model.vtt 10.5 kB
  • 4. Word Embeddings and Word2Vec/10. Word2Vec in Code with Numpy.vtt 10.5 kB
  • 3. Review of Language Modeling and Neural Networks/6. Neural Network Bigram Model.vtt 10.2 kB
  • 7. Using Neural Networks to Solve NLP Problems/6. How does an HMM solve POS tagging.vtt 9.8 kB
  • 4. Word Embeddings and Word2Vec/4. Hierarchical Softmax.vtt 9.7 kB
  • 2. Beginner's Corner Working with Word Vectors/1. What are vectors.vtt 9.3 kB
  • 4. Word Embeddings and Word2Vec/2. CBOW.vtt 9.2 kB
  • 2. Beginner's Corner Working with Word Vectors/2. What is a word analogy.vtt 9.2 kB
  • 8. Recursive Neural Networks (Tree Neural Networks)/3. Data Description for Recursive Neural Networks.vtt 9.1 kB
  • 5. Word Embeddings using GloVe/3. Matrix Factorization Training.vtt 9.0 kB
  • 3. Review of Language Modeling and Neural Networks/4. Neural Bigram Model.vtt 8.7 kB
  • 8. Recursive Neural Networks (Tree Neural Networks)/1. Recursive Neural Networks Section Introduction.vtt 8.6 kB
  • 7. Using Neural Networks to Solve NLP Problems/4. Parts-of-Speech Tagging Recurrent Neural Network in Theano.vtt 8.2 kB
  • 8. Recursive Neural Networks (Tree Neural Networks)/6. Trees to Sequences.vtt 8.2 kB
  • 1. Outline, Review, and Logistical Things/1. Introduction, Outline, and Review.vtt 7.9 kB
  • 8. Recursive Neural Networks (Tree Neural Networks)/8. Recursive Neural Tensor Networks.vtt 7.7 kB
  • 6. Unifying Word2Vec and GloVe/2. PMI in Code.vtt 7.5 kB
  • 2. Beginner's Corner Working with Word Vectors/3. Trying to find and assess word vectors using TF-IDF and t-SNE.vtt 7.5 kB
  • 8. Recursive Neural Networks (Tree Neural Networks)/4. What are Recursive Neural Networks Tree Neural Networks (TNNs).vtt 7.2 kB
  • 4. Word Embeddings and Word2Vec/15. Alternative to Wikipedia Data Brown Corpus.vtt 7.2 kB
  • 2. Beginner's Corner Working with Word Vectors/5. Pretrained word vectors from word2vec.vtt 7.1 kB
  • 4. Word Embeddings and Word2Vec/13. How to update only part of a Theano shared variable.vtt 7.1 kB
  • 3. Review of Language Modeling and Neural Networks/5. Neural Bigram Model in Code.vtt 7.0 kB
  • 5. Word Embeddings using GloVe/11. GloVe in Tensorflow with Gradient Descent.vtt 7.0 kB
  • 5. Word Embeddings using GloVe/5. Regularization for Matrix Factorization.vtt 6.7 kB
  • 4. Word Embeddings and Word2Vec/14. Word2Vec in Code with Theano.vtt 6.6 kB
  • 2. Beginner's Corner Working with Word Vectors/7. Text Classification in Code.vtt 6.6 kB
  • 9. Theano and Tensorflow Basics Review/1. (Review) Theano Basics.vtt 6.5 kB
  • 8. Recursive Neural Networks (Tree Neural Networks)/2. Sentences as Trees.vtt 6.4 kB
  • 10. Legacy Word2vec Lectures/5. (Legacy) Word2Vec introduction.vtt 6.3 kB
  • 8. Recursive Neural Networks (Tree Neural Networks)/5. Building a TNN with Recursion.vtt 6.1 kB
  • 7. Using Neural Networks to Solve NLP Problems/1. Parts-of-Speech (POS) Tagging.vtt 6.1 kB
  • 4. Word Embeddings and Word2Vec/6. Negative Sampling - Important Details.vtt 6.0 kB
  • 4. Word Embeddings and Word2Vec/8. Word2Vec implementation tricks.vtt 5.5 kB
  • 11. Appendix/11. Python 2 vs Python 3.vtt 5.5 kB
  • 5. Word Embeddings using GloVe/6. GloVe - Global Vectors for Word Representation.vtt 5.2 kB
  • 9. Theano and Tensorflow Basics Review/3. (Review) Tensorflow Basics.vtt 5.2 kB
  • 3. Review of Language Modeling and Neural Networks/9. Improving Efficiency in Code.vtt 5.2 kB
  • 4. Word Embeddings and Word2Vec/9. Word2Vec implementation outline.vtt 5.0 kB
  • 10. Legacy Word2vec Lectures/3. (Legacy) Word analogies using word embeddings.vtt 5.0 kB
  • 7. Using Neural Networks to Solve NLP Problems/2. How can neural networks be used to solve POS tagging.vtt 4.9 kB
  • 2. Beginner's Corner Working with Word Vectors/6. Text Classification with word vectors.vtt 4.9 kB
  • 8. Recursive Neural Networks (Tree Neural Networks)/11. Recursive Neural Network in TensorFlow with Recursion.vtt 4.9 kB
  • 9. Theano and Tensorflow Basics Review/4. (Review) Tensorflow Neural Network in Code.vtt 4.9 kB
  • 1. Outline, Review, and Logistical Things/4. Tensorflow or Theano - Your Choice!.vtt 4.9 kB
  • 7. Using Neural Networks to Solve NLP Problems/7. Parts-of-Speech Tagging Hidden Markov Model (HMM).vtt 4.7 kB
  • 4. Word Embeddings and Word2Vec/3. Skip-Gram.vtt 4.6 kB
  • 4. Word Embeddings and Word2Vec/11. Word2Vec Tensorflow Implementation Details.vtt 4.5 kB
  • 7. Using Neural Networks to Solve NLP Problems/10. Named Entity Recognition Baseline.vtt 4.0 kB
  • 3. Review of Language Modeling and Neural Networks/10. Review Section Summary.vtt 3.9 kB
  • 7. Using Neural Networks to Solve NLP Problems/8. Named Entity Recognition (NER).vtt 3.9 kB
  • 2. Beginner's Corner Working with Word Vectors/8. Using pretrained vectors later in the course.vtt 3.9 kB
  • 3. Review of Language Modeling and Neural Networks/1. Review Section Intro.vtt 3.9 kB
  • 3. Review of Language Modeling and Neural Networks/7. Neural Network Bigram Model in Code.vtt 3.6 kB
  • 1. Outline, Review, and Logistical Things/3. How to Succeed in this Course.vtt 3.6 kB
  • 4. Word Embeddings and Word2Vec/1. Return of the Bigram.vtt 3.4 kB
  • 9. Theano and Tensorflow Basics Review/2. (Review) Theano Neural Network in Code.vtt 3.4 kB
  • 11. Appendix/1. What is the Appendix.vtt 3.4 kB
  • 5. Word Embeddings using GloVe/12. Visualizing country analogies with t-SNE.vtt 3.3 kB
  • 4. Word Embeddings and Word2Vec/12. Word2Vec Tensorflow in Code.vtt 3.3 kB
  • 11. Appendix/10. BONUS Where to get Udemy coupons and FREE deep learning material.vtt 3.1 kB
  • 5. Word Embeddings using GloVe/13. Hyperparameter Challenge.vtt 3.0 kB
  • 11. Appendix/2. How to install wp2txt or WikiExtractor.py.vtt 2.9 kB
  • 10. Legacy Word2vec Lectures/2. (Legacy) Using pre-trained word embeddings.vtt 2.9 kB
  • 5. Word Embeddings using GloVe/7. Recap of ways to train GloVe.vtt 2.9 kB
  • 7. Using Neural Networks to Solve NLP Problems/13. Hyperparameter Challenge II.vtt 2.9 kB
  • 5. Word Embeddings using GloVe/9. GloVe in Code - Alternating Least Squares.vtt 2.7 kB
  • 5. Word Embeddings using GloVe/1. GloVe Section Introduction.vtt 2.6 kB
  • 4. Word Embeddings and Word2Vec/7. Why do I have 2 word embedding matrices and what do I do with them.vtt 2.6 kB
  • 5. Word Embeddings using GloVe/10. GloVe in Code - Theano Gradient Descent.vtt 2.4 kB
  • 7. Using Neural Networks to Solve NLP Problems/9. Comparing NER and POS tagging.vtt 2.4 kB
  • 7. Using Neural Networks to Solve NLP Problems/12. Named Entity Recognition RNN in Tensorflow.vtt 2.2 kB
  • 1. Outline, Review, and Logistical Things/2. Where to get the code data for this course.vtt 2.0 kB
  • 7. Using Neural Networks to Solve NLP Problems/11. Named Entity Recognition RNN in Theano.vtt 1.5 kB

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