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[FreeCourseLab.com] Udemy - Natural Language Processing with Deep Learning in Python

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视频 2023-2-14 18:32 2024-5-5 19:54 155 3.12 GB 100
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FreeCourseLab com Udemy - Natural Language Processing with Deep Learning in Python

文件列表
  1. 1. Outline, Review, and Logistical Things/1. Introduction, Outline, and Review.mp437.13MB
  2. 1. Outline, Review, and Logistical Things/2. Where to get the code data for this course.mp46.5MB
  3. 1. Outline, Review, and Logistical Things/3. How to Succeed in this Course.mp43.3MB
  4. 1. Outline, Review, and Logistical Things/4. Tensorflow or Theano - Your Choice!.mp418.58MB
  5. 10. Legacy Word2vec Lectures/1. (Legacy) What is a word embedding.mp418MB
  6. 10. Legacy Word2vec Lectures/2. (Legacy) Using pre-trained word embeddings.mp44.05MB
  7. 10. Legacy Word2vec Lectures/3. (Legacy) Word analogies using word embeddings.mp46.61MB
  8. 10. Legacy Word2vec Lectures/4. (Legacy) TF-IDF and t-SNE experiment.mp426.76MB
  9. 10. Legacy Word2vec Lectures/5. (Legacy) Word2Vec introduction.mp48.82MB
  10. 11. Appendix/1. What is the Appendix.mp45.45MB
  11. 11. Appendix/10. BONUS Where to get Udemy coupons and FREE deep learning material.mp44.02MB
  12. 11. Appendix/11. Python 2 vs Python 3.mp47.84MB
  13. 11. Appendix/12. Is Theano Dead.mp417.81MB
  14. 11. Appendix/13. What order should I take your courses in (part 1).mp429.33MB
  15. 11. Appendix/14. What order should I take your courses in (part 2).mp437.62MB
  16. 11. Appendix/2. How to install wp2txt or WikiExtractor.py.mp43.77MB
  17. 11. Appendix/3. Windows-Focused Environment Setup 2018.mp4186.39MB
  18. 11. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp443.92MB
  19. 11. Appendix/5. How to Code by Yourself (part 1).mp424.53MB
  20. 11. Appendix/6. How to Code by Yourself (part 2).mp414.8MB
  21. 11. Appendix/7. How to Succeed in this Course (Long Version).mp412.99MB
  22. 11. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp438.95MB
  23. 11. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp478.27MB
  24. 2. Beginner's Corner Working with Word Vectors/1. What are vectors.mp435.35MB
  25. 2. Beginner's Corner Working with Word Vectors/2. What is a word analogy.mp431.21MB
  26. 2. Beginner's Corner Working with Word Vectors/3. Trying to find and assess word vectors using TF-IDF and t-SNE.mp432.14MB
  27. 2. Beginner's Corner Working with Word Vectors/4. Pretrained word vectors from GloVe.mp497.5MB
  28. 2. Beginner's Corner Working with Word Vectors/5. Pretrained word vectors from word2vec.mp463.24MB
  29. 2. Beginner's Corner Working with Word Vectors/6. Text Classification with word vectors.mp420.62MB
  30. 2. Beginner's Corner Working with Word Vectors/7. Text Classification in Code.mp454.6MB
  31. 2. Beginner's Corner Working with Word Vectors/8. Using pretrained vectors later in the course.mp413.87MB
  32. 3. Review of Language Modeling and Neural Networks/1. Review Section Intro.mp45.55MB
  33. 3. Review of Language Modeling and Neural Networks/10. Review Section Summary.mp42.98MB
  34. 3. Review of Language Modeling and Neural Networks/2. Bigrams and Language Models.mp412.24MB
  35. 3. Review of Language Modeling and Neural Networks/3. Bigrams in Code.mp417.89MB
  36. 3. Review of Language Modeling and Neural Networks/4. Neural Bigram Model.mp439.72MB
  37. 3. Review of Language Modeling and Neural Networks/5. Neural Bigram Model in Code.mp48.3MB
  38. 3. Review of Language Modeling and Neural Networks/6. Neural Network Bigram Model.mp48.03MB
  39. 3. Review of Language Modeling and Neural Networks/7. Neural Network Bigram Model in Code.mp45.17MB
  40. 3. Review of Language Modeling and Neural Networks/8. Improving Efficiency.mp411.92MB
  41. 3. Review of Language Modeling and Neural Networks/9. Improving Efficiency in Code.mp46.75MB
  42. 4. Word Embeddings and Word2Vec/1. Return of the Bigram.mp411.5MB
  43. 4. Word Embeddings and Word2Vec/10. Word2Vec in Code with Numpy.mp4108.24MB
  44. 4. Word Embeddings and Word2Vec/11. Word2Vec Tensorflow Implementation Details.mp412.83MB
  45. 4. Word Embeddings and Word2Vec/12. Word2Vec Tensorflow in Code.mp444.15MB
  46. 4. Word Embeddings and Word2Vec/13. How to update only part of a Theano shared variable.mp49.19MB
  47. 4. Word Embeddings and Word2Vec/14. Word2Vec in Code with Theano.mp431.05MB
  48. 4. Word Embeddings and Word2Vec/15. Alternative to Wikipedia Data Brown Corpus.mp412.49MB
  49. 4. Word Embeddings and Word2Vec/2. CBOW.mp436.5MB
  50. 4. Word Embeddings and Word2Vec/3. Skip-Gram.mp416.06MB
  51. 4. Word Embeddings and Word2Vec/4. Hierarchical Softmax.mp431.24MB
  52. 4. Word Embeddings and Word2Vec/5. Negative Sampling.mp459.18MB
  53. 4. Word Embeddings and Word2Vec/6. Negative Sampling - Important Details.mp418.67MB
  54. 4. Word Embeddings and Word2Vec/7. Why do I have 2 word embedding matrices and what do I do with them.mp45.5MB
  55. 4. Word Embeddings and Word2Vec/8. Word2Vec implementation tricks.mp415.67MB
  56. 4. Word Embeddings and Word2Vec/9. Word2Vec implementation outline.mp414.46MB
  57. 5. Word Embeddings using GloVe/1. GloVe Section Introduction.mp417.24MB
  58. 5. Word Embeddings using GloVe/10. GloVe in Code - Theano Gradient Descent.mp444.03MB
  59. 5. Word Embeddings using GloVe/11. GloVe in Tensorflow with Gradient Descent.mp474.91MB
  60. 5. Word Embeddings using GloVe/12. Visualizing country analogies with t-SNE.mp49.18MB
  61. 5. Word Embeddings using GloVe/13. Hyperparameter Challenge.mp44.04MB
  62. 5. Word Embeddings using GloVe/14. Training GloVe with SVD (Singular Value Decomposition).mp451.98MB
  63. 5. Word Embeddings using GloVe/2. Matrix Factorization for Recommender Systems - Basic Concepts.mp490.16MB
  64. 5. Word Embeddings using GloVe/3. Matrix Factorization Training.mp428.75MB
  65. 5. Word Embeddings using GloVe/4. Expanding the Matrix Factorization Model.mp440.94MB
  66. 5. Word Embeddings using GloVe/5. Regularization for Matrix Factorization.mp422.3MB
  67. 5. Word Embeddings using GloVe/6. GloVe - Global Vectors for Word Representation.mp47.06MB
  68. 5. Word Embeddings using GloVe/7. Recap of ways to train GloVe.mp415.99MB
  69. 5. Word Embeddings using GloVe/8. GloVe in Code - Numpy Gradient Descent.mp441.85MB
  70. 5. Word Embeddings using GloVe/9. GloVe in Code - Alternating Least Squares.mp411.65MB
  71. 6. Unifying Word2Vec and GloVe/1. Pointwise Mutual Information - Word2Vec as Matrix Factorization.mp453.27MB
  72. 6. Unifying Word2Vec and GloVe/2. PMI in Code.mp473.12MB
  73. 7. Using Neural Networks to Solve NLP Problems/1. Parts-of-Speech (POS) Tagging.mp47.75MB
  74. 7. Using Neural Networks to Solve NLP Problems/10. Named Entity Recognition Baseline.mp414.91MB
  75. 7. Using Neural Networks to Solve NLP Problems/11. Named Entity Recognition RNN in Theano.mp45.39MB
  76. 7. Using Neural Networks to Solve NLP Problems/12. Named Entity Recognition RNN in Tensorflow.mp428.54MB
  77. 7. Using Neural Networks to Solve NLP Problems/13. Hyperparameter Challenge II.mp43.83MB
  78. 7. Using Neural Networks to Solve NLP Problems/2. How can neural networks be used to solve POS tagging.mp416.88MB
  79. 7. Using Neural Networks to Solve NLP Problems/3. Parts-of-Speech Tagging Baseline.mp439.87MB
  80. 7. Using Neural Networks to Solve NLP Problems/4. Parts-of-Speech Tagging Recurrent Neural Network in Theano.mp434.81MB
  81. 7. Using Neural Networks to Solve NLP Problems/5. Parts-of-Speech Tagging Recurrent Neural Network in Tensorflow.mp4129.45MB
  82. 7. Using Neural Networks to Solve NLP Problems/6. How does an HMM solve POS tagging.mp445.24MB
  83. 7. Using Neural Networks to Solve NLP Problems/7. Parts-of-Speech Tagging Hidden Markov Model (HMM).mp414.39MB
  84. 7. Using Neural Networks to Solve NLP Problems/8. Named Entity Recognition (NER).mp44.96MB
  85. 7. Using Neural Networks to Solve NLP Problems/9. Comparing NER and POS tagging.mp414.31MB
  86. 8. Recursive Neural Networks (Tree Neural Networks)/1. Recursive Neural Networks Section Introduction.mp437.4MB
  87. 8. Recursive Neural Networks (Tree Neural Networks)/10. RNTN in Tensorflow (Code).mp4133.43MB
  88. 8. Recursive Neural Networks (Tree Neural Networks)/11. Recursive Neural Network in TensorFlow with Recursion.mp412.74MB
  89. 8. Recursive Neural Networks (Tree Neural Networks)/2. Sentences as Trees.mp424.2MB
  90. 8. Recursive Neural Networks (Tree Neural Networks)/3. Data Description for Recursive Neural Networks.mp411.54MB
  91. 8. Recursive Neural Networks (Tree Neural Networks)/4. What are Recursive Neural Networks Tree Neural Networks (TNNs).mp49.52MB
  92. 8. Recursive Neural Networks (Tree Neural Networks)/5. Building a TNN with Recursion.mp48.1MB
  93. 8. Recursive Neural Networks (Tree Neural Networks)/6. Trees to Sequences.mp411.17MB
  94. 8. Recursive Neural Networks (Tree Neural Networks)/7. Recursive Neural Network in Theano.mp452.51MB
  95. 8. Recursive Neural Networks (Tree Neural Networks)/8. Recursive Neural Tensor Networks.mp411.1MB
  96. 8. Recursive Neural Networks (Tree Neural Networks)/9. RNTN in Tensorflow (Tips).mp449.51MB
  97. 9. Theano and Tensorflow Basics Review/1. (Review) Theano Basics.mp493.45MB
  98. 9. Theano and Tensorflow Basics Review/2. (Review) Theano Neural Network in Code.mp487.02MB
  99. 9. Theano and Tensorflow Basics Review/3. (Review) Tensorflow Basics.mp481.45MB
  100. 9. Theano and Tensorflow Basics Review/4. (Review) Tensorflow Neural Network in Code.mp497.37MB
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