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

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文件列表

  1. 11. Appendix FAQ/4. Windows-Focused Environment Setup 2018.mp4 186MB
  2. 8. Recursive Neural Networks (Tree Neural Networks)/10. RNTN in Tensorflow (Code).mp4 133MB
  3. 7. Using Neural Networks to Solve NLP Problems/5. Parts-of-Speech Tagging Recurrent Neural Network in Tensorflow.mp4 129MB
  4. 4. Word Embeddings and Word2Vec/10. Word2Vec in Code with Numpy.mp4 108MB
  5. 2. Beginner's Corner Working with Word Vectors/4. Pretrained word vectors from GloVe.mp4 97MB
  6. 9. Theano and Tensorflow Basics Review/4. (Review) Tensorflow Neural Network in Code.mp4 97MB
  7. 9. Theano and Tensorflow Basics Review/1. (Review) Theano Basics.mp4 93MB
  8. 5. Word Embeddings using GloVe/2. Matrix Factorization for Recommender Systems - Basic Concepts.mp4 90MB
  9. 9. Theano and Tensorflow Basics Review/2. (Review) Theano Neural Network in Code.mp4 87MB
  10. 9. Theano and Tensorflow Basics Review/3. (Review) Tensorflow Basics.mp4 81MB
  11. 11. Appendix FAQ/10. Proof that using Jupyter Notebook is the same as not using it.mp4 78MB
  12. 5. Word Embeddings using GloVe/11. GloVe in Tensorflow with Gradient Descent.mp4 75MB
  13. 6. Unifying Word2Vec and GloVe/2. PMI in Code.mp4 73MB
  14. 2. Beginner's Corner Working with Word Vectors/5. Pretrained word vectors from word2vec.mp4 63MB
  15. 4. Word Embeddings and Word2Vec/5. Negative Sampling.mp4 59MB
  16. 2. Beginner's Corner Working with Word Vectors/7. Text Classification in Code.mp4 55MB
  17. 6. Unifying Word2Vec and GloVe/1. Pointwise Mutual Information - Word2Vec as Matrix Factorization.mp4 53MB
  18. 8. Recursive Neural Networks (Tree Neural Networks)/7. Recursive Neural Network in Theano.mp4 53MB
  19. 5. Word Embeddings using GloVe/14. Training GloVe with SVD (Singular Value Decomposition).mp4 52MB
  20. 8. Recursive Neural Networks (Tree Neural Networks)/9. RNTN in Tensorflow (Tips).mp4 50MB
  21. 7. Using Neural Networks to Solve NLP Problems/6. How does an HMM solve POS tagging.mp4 45MB
  22. 4. Word Embeddings and Word2Vec/12. Word2Vec Tensorflow in Code.mp4 44MB
  23. 5. Word Embeddings using GloVe/10. GloVe in Code - Theano Gradient Descent.mp4 44MB
  24. 11. Appendix FAQ/5. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 44MB
  25. 5. Word Embeddings using GloVe/8. GloVe in Code - Numpy Gradient Descent.mp4 42MB
  26. 5. Word Embeddings using GloVe/4. Expanding the Matrix Factorization Model.mp4 41MB
  27. 7. Using Neural Networks to Solve NLP Problems/3. Parts-of-Speech Tagging Baseline.mp4 40MB
  28. 3. Review of Language Modeling and Neural Networks/4. Neural Bigram Model.mp4 40MB
  29. 11. Appendix FAQ/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39MB
  30. 11. Appendix FAQ/11. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 38MB
  31. 11. Appendix FAQ/15. What order should I take your courses in (part 2).mp4 38MB
  32. 8. Recursive Neural Networks (Tree Neural Networks)/1. Recursive Neural Networks Section Introduction.mp4 37MB
  33. 1. Outline, Review, and Logistical Things/1. Introduction, Outline, and Review.mp4 37MB
  34. 4. Word Embeddings and Word2Vec/2. CBOW.mp4 37MB
  35. 2. Beginner's Corner Working with Word Vectors/1. What are vectors.mp4 35MB
  36. 7. Using Neural Networks to Solve NLP Problems/4. Parts-of-Speech Tagging Recurrent Neural Network in Theano.mp4 35MB
  37. 2. Beginner's Corner Working with Word Vectors/3. Trying to find and assess word vectors using TF-IDF and t-SNE.mp4 32MB
  38. 4. Word Embeddings and Word2Vec/4. Hierarchical Softmax.mp4 31MB
  39. 2. Beginner's Corner Working with Word Vectors/2. What is a word analogy.mp4 31MB
  40. 4. Word Embeddings and Word2Vec/14. Word2Vec in Code with Theano.mp4 31MB
  41. 11. Appendix FAQ/14. What order should I take your courses in (part 1).mp4 29MB
  42. 5. Word Embeddings using GloVe/3. Matrix Factorization Training.mp4 29MB
  43. 7. Using Neural Networks to Solve NLP Problems/12. Named Entity Recognition RNN in Tensorflow.mp4 29MB
  44. 10. Legacy Word2vec Lectures/4. (Legacy) TF-IDF and t-SNE experiment.mp4 27MB
  45. 11. Appendix FAQ/6. How to Code by Yourself (part 1).mp4 25MB
  46. 8. Recursive Neural Networks (Tree Neural Networks)/2. Sentences as Trees.mp4 24MB
  47. 5. Word Embeddings using GloVe/5. Regularization for Matrix Factorization.mp4 22MB
  48. 1. Outline, Review, and Logistical Things/5. Preprocessed Wikipedia Data.mp4 22MB
  49. 2. Beginner's Corner Working with Word Vectors/6. Text Classification with word vectors.mp4 21MB
  50. 4. Word Embeddings and Word2Vec/6. Negative Sampling - Important Details.mp4 19MB
  51. 1. Outline, Review, and Logistical Things/3. Tensorflow or Theano - Your Choice!.mp4 19MB
  52. 10. Legacy Word2vec Lectures/1. (Legacy) What is a word embedding.mp4 18MB
  53. 3. Review of Language Modeling and Neural Networks/3. Bigrams in Code.mp4 18MB
  54. 11. Appendix FAQ/13. Is Theano Dead.mp4 18MB
  55. 5. Word Embeddings using GloVe/1. GloVe Section Introduction.mp4 17MB
  56. 7. Using Neural Networks to Solve NLP Problems/2. How can neural networks be used to solve POS tagging.mp4 17MB
  57. 4. Word Embeddings and Word2Vec/3. Skip-Gram.mp4 16MB
  58. 5. Word Embeddings using GloVe/7. Recap of ways to train GloVe.mp4 16MB
  59. 4. Word Embeddings and Word2Vec/8. Word2Vec implementation tricks.mp4 16MB
  60. 7. Using Neural Networks to Solve NLP Problems/10. Named Entity Recognition Baseline.mp4 15MB
  61. 11. Appendix FAQ/7. How to Code by Yourself (part 2).mp4 15MB
  62. 4. Word Embeddings and Word2Vec/9. Word2Vec implementation outline.mp4 14MB
  63. 7. Using Neural Networks to Solve NLP Problems/7. Parts-of-Speech Tagging Hidden Markov Model (HMM).mp4 14MB
  64. 7. Using Neural Networks to Solve NLP Problems/9. Comparing NER and POS tagging.mp4 14MB
  65. 2. Beginner's Corner Working with Word Vectors/8. Using pretrained vectors later in the course.mp4 14MB
  66. 11. Appendix FAQ/8. How to Succeed in this Course (Long Version).mp4 13MB
  67. 11. Appendix FAQ/3. How to Uncompress a .tar.gz file.mp4 13MB
  68. 4. Word Embeddings and Word2Vec/11. Word2Vec Tensorflow Implementation Details.mp4 13MB
  69. 8. Recursive Neural Networks (Tree Neural Networks)/11. Recursive Neural Network in TensorFlow with Recursion.mp4 13MB
  70. 4. Word Embeddings and Word2Vec/15. Alternative to Wikipedia Data Brown Corpus.mp4 12MB
  71. 3. Review of Language Modeling and Neural Networks/2. Bigrams and Language Models.mp4 12MB
  72. 3. Review of Language Modeling and Neural Networks/8. Improving Efficiency.mp4 12MB
  73. 5. Word Embeddings using GloVe/9. GloVe in Code - Alternating Least Squares.mp4 12MB
  74. 8. Recursive Neural Networks (Tree Neural Networks)/3. Data Description for Recursive Neural Networks.mp4 12MB
  75. 4. Word Embeddings and Word2Vec/1. Return of the Bigram.mp4 12MB
  76. 8. Recursive Neural Networks (Tree Neural Networks)/6. Trees to Sequences.mp4 11MB
  77. 8. Recursive Neural Networks (Tree Neural Networks)/8. Recursive Neural Tensor Networks.mp4 11MB
  78. 8. Recursive Neural Networks (Tree Neural Networks)/4. What are Recursive Neural Networks Tree Neural Networks (TNNs).mp4 10MB
  79. 4. Word Embeddings and Word2Vec/13. How to update only part of a Theano shared variable.mp4 9MB
  80. 5. Word Embeddings using GloVe/12. Visualizing country analogies with t-SNE.mp4 9MB
  81. 10. Legacy Word2vec Lectures/5. (Legacy) Word2Vec introduction.mp4 9MB
  82. 3. Review of Language Modeling and Neural Networks/5. Neural Bigram Model in Code.mp4 8MB
  83. 8. Recursive Neural Networks (Tree Neural Networks)/5. Building a TNN with Recursion.mp4 8MB
  84. 3. Review of Language Modeling and Neural Networks/6. Neural Network Bigram Model.mp4 8MB
  85. 11. Appendix FAQ/12. Python 2 vs Python 3.mp4 8MB
  86. 7. Using Neural Networks to Solve NLP Problems/1. Parts-of-Speech (POS) Tagging.mp4 8MB
  87. 5. Word Embeddings using GloVe/6. GloVe - Global Vectors for Word Representation.mp4 7MB
  88. 3. Review of Language Modeling and Neural Networks/9. Improving Efficiency in Code.mp4 7MB
  89. 10. Legacy Word2vec Lectures/3. (Legacy) Word analogies using word embeddings.mp4 7MB
  90. 1. Outline, Review, and Logistical Things/4. Where to get the code data for this course.mp4 7MB
  91. 3. Review of Language Modeling and Neural Networks/1. Review Section Intro.mp4 6MB
  92. 4. Word Embeddings and Word2Vec/7. Why do I have 2 word embedding matrices and what do I do with them.mp4 5MB
  93. 11. Appendix FAQ/1. What is the Appendix.mp4 5MB
  94. 7. Using Neural Networks to Solve NLP Problems/11. Named Entity Recognition RNN in Theano.mp4 5MB
  95. 3. Review of Language Modeling and Neural Networks/7. Neural Network Bigram Model in Code.mp4 5MB
  96. 7. Using Neural Networks to Solve NLP Problems/8. Named Entity Recognition (NER).mp4 5MB
  97. 10. Legacy Word2vec Lectures/2. (Legacy) Using pre-trained word embeddings.mp4 4MB
  98. 5. Word Embeddings using GloVe/13. Hyperparameter Challenge.mp4 4MB
  99. 7. Using Neural Networks to Solve NLP Problems/13. Hyperparameter Challenge II.mp4 4MB
  100. 11. Appendix FAQ/2. How to install wp2txt or WikiExtractor.py.mp4 4MB
  101. 1. Outline, Review, and Logistical Things/2. How to Succeed in this Course.mp4 3MB
  102. 3. Review of Language Modeling and Neural Networks/10. Review Section Summary.mp4 3MB
  103. 11. Appendix FAQ/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 32KB
  104. 5. Word Embeddings using GloVe/2. Matrix Factorization for Recommender Systems - Basic Concepts.srt 27KB
  105. 11. Appendix FAQ/15. What order should I take your courses in (part 2).srt 23KB
  106. 11. Appendix FAQ/6. How to Code by Yourself (part 1).srt 23KB
  107. 11. Appendix FAQ/4. Windows-Focused Environment Setup 2018.srt 20KB
  108. 4. Word Embeddings and Word2Vec/5. Negative Sampling.srt 18KB
  109. 3. Review of Language Modeling and Neural Networks/8. Improving Efficiency.srt 18KB
  110. 3. Review of Language Modeling and Neural Networks/3. Bigrams in Code.srt 17KB
  111. 3. Review of Language Modeling and Neural Networks/2. Bigrams and Language Models.srt 17KB
  112. 7. Using Neural Networks to Solve NLP Problems/5. Parts-of-Speech Tagging Recurrent Neural Network in Tensorflow.srt 16KB
  113. 8. Recursive Neural Networks (Tree Neural Networks)/7. Recursive Neural Network in Theano.srt 16KB
  114. 11. Appendix FAQ/14. What order should I take your courses in (part 1).srt 16KB
  115. 8. Recursive Neural Networks (Tree Neural Networks)/9. RNTN in Tensorflow (Tips).srt 16KB
  116. 6. Unifying Word2Vec and GloVe/1. Pointwise Mutual Information - Word2Vec as Matrix Factorization.srt 16KB
  117. 11. Appendix FAQ/8. How to Succeed in this Course (Long Version).srt 15KB
  118. 5. Word Embeddings using GloVe/8. GloVe in Code - Numpy Gradient Descent.srt 15KB
  119. 11. Appendix FAQ/5. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14KB
  120. 2. Beginner's Corner Working with Word Vectors/4. Pretrained word vectors from GloVe.srt 14KB
  121. 11. Appendix FAQ/10. Proof that using Jupyter Notebook is the same as not using it.srt 14KB
  122. 10. Legacy Word2vec Lectures/1. (Legacy) What is a word embedding.srt 14KB
  123. 8. Recursive Neural Networks (Tree Neural Networks)/10. RNTN in Tensorflow (Code).srt 13KB
  124. 11. Appendix FAQ/7. How to Code by Yourself (part 2).srt 13KB
  125. 11. Appendix FAQ/13. Is Theano Dead.srt 13KB
  126. 10. Legacy Word2vec Lectures/4. (Legacy) TF-IDF and t-SNE experiment.srt 13KB
  127. 5. Word Embeddings using GloVe/14. Training GloVe with SVD (Singular Value Decomposition).srt 12KB
  128. 7. Using Neural Networks to Solve NLP Problems/3. Parts-of-Speech Tagging Baseline.srt 12KB
  129. 5. Word Embeddings using GloVe/4. Expanding the Matrix Factorization Model.srt 12KB
  130. 4. Word Embeddings and Word2Vec/10. Word2Vec in Code with Numpy.srt 12KB
  131. 3. Review of Language Modeling and Neural Networks/6. Neural Network Bigram Model.srt 11KB
  132. 7. Using Neural Networks to Solve NLP Problems/6. How does an HMM solve POS tagging.srt 11KB
  133. 4. Word Embeddings and Word2Vec/4. Hierarchical Softmax.srt 11KB
  134. 2. Beginner's Corner Working with Word Vectors/1. What are vectors.srt 10KB
  135. 2. Beginner's Corner Working with Word Vectors/2. What is a word analogy.srt 10KB
  136. 4. Word Embeddings and Word2Vec/2. CBOW.srt 10KB
  137. 5. Word Embeddings using GloVe/3. Matrix Factorization Training.srt 10KB
  138. 8. Recursive Neural Networks (Tree Neural Networks)/3. Data Description for Recursive Neural Networks.srt 10KB
  139. 3. Review of Language Modeling and Neural Networks/4. Neural Bigram Model.srt 10KB
  140. 8. Recursive Neural Networks (Tree Neural Networks)/1. Recursive Neural Networks Section Introduction.srt 10KB
  141. 7. Using Neural Networks to Solve NLP Problems/4. Parts-of-Speech Tagging Recurrent Neural Network in Theano.srt 9KB
  142. 8. Recursive Neural Networks (Tree Neural Networks)/6. Trees to Sequences.srt 9KB
  143. 1. Outline, Review, and Logistical Things/1. Introduction, Outline, and Review.srt 9KB
  144. 8. Recursive Neural Networks (Tree Neural Networks)/8. Recursive Neural Tensor Networks.srt 8KB
  145. 2. Beginner's Corner Working with Word Vectors/3. Trying to find and assess word vectors using TF-IDF and t-SNE.srt 8KB
  146. 6. Unifying Word2Vec and GloVe/2. PMI in Code.srt 8KB
  147. 2. Beginner's Corner Working with Word Vectors/5. Pretrained word vectors from word2vec.srt 8KB
  148. 4. Word Embeddings and Word2Vec/15. Alternative to Wikipedia Data Brown Corpus.srt 8KB
  149. 11. Appendix FAQ/11. BONUS Where to get Udemy coupons and FREE deep learning material.srt 8KB
  150. 3. Review of Language Modeling and Neural Networks/5. Neural Bigram Model in Code.srt 8KB
  151. 5. Word Embeddings using GloVe/11. GloVe in Tensorflow with Gradient Descent.srt 8KB
  152. 8. Recursive Neural Networks (Tree Neural Networks)/4. What are Recursive Neural Networks Tree Neural Networks (TNNs).srt 8KB
  153. 4. Word Embeddings and Word2Vec/13. How to update only part of a Theano shared variable.srt 8KB
  154. 5. Word Embeddings using GloVe/5. Regularization for Matrix Factorization.srt 7KB
  155. 2. Beginner's Corner Working with Word Vectors/7. Text Classification in Code.srt 7KB
  156. 4. Word Embeddings and Word2Vec/14. Word2Vec in Code with Theano.srt 7KB
  157. 9. Theano and Tensorflow Basics Review/1. (Review) Theano Basics.srt 7KB
  158. 8. Recursive Neural Networks (Tree Neural Networks)/2. Sentences as Trees.srt 7KB
  159. 10. Legacy Word2vec Lectures/5. (Legacy) Word2Vec introduction.srt 7KB
  160. 7. Using Neural Networks to Solve NLP Problems/1. Parts-of-Speech (POS) Tagging.srt 7KB
  161. 4. Word Embeddings and Word2Vec/6. Negative Sampling - Important Details.srt 7KB
  162. 8. Recursive Neural Networks (Tree Neural Networks)/5. Building a TNN with Recursion.srt 7KB
  163. 4. Word Embeddings and Word2Vec/8. Word2Vec implementation tricks.srt 6KB
  164. 11. Appendix FAQ/12. Python 2 vs Python 3.srt 6KB
  165. 9. Theano and Tensorflow Basics Review/3. (Review) Tensorflow Basics.srt 6KB
  166. 3. Review of Language Modeling and Neural Networks/9. Improving Efficiency in Code.srt 6KB
  167. 5. Word Embeddings using GloVe/6. GloVe - Global Vectors for Word Representation.srt 6KB
  168. 4. Word Embeddings and Word2Vec/9. Word2Vec implementation outline.srt 6KB
  169. 9. Theano and Tensorflow Basics Review/4. (Review) Tensorflow Neural Network in Code.srt 6KB
  170. 7. Using Neural Networks to Solve NLP Problems/2. How can neural networks be used to solve POS tagging.srt 5KB
  171. 2. Beginner's Corner Working with Word Vectors/6. Text Classification with word vectors.srt 5KB
  172. 10. Legacy Word2vec Lectures/3. (Legacy) Word analogies using word embeddings.srt 5KB
  173. 1. Outline, Review, and Logistical Things/3. Tensorflow or Theano - Your Choice!.srt 5KB
  174. 8. Recursive Neural Networks (Tree Neural Networks)/11. Recursive Neural Network in TensorFlow with Recursion.srt 5KB
  175. 7. Using Neural Networks to Solve NLP Problems/7. Parts-of-Speech Tagging Hidden Markov Model (HMM).srt 5KB
  176. 4. Word Embeddings and Word2Vec/3. Skip-Gram.srt 5KB
  177. 4. Word Embeddings and Word2Vec/11. Word2Vec Tensorflow Implementation Details.srt 5KB
  178. 7. Using Neural Networks to Solve NLP Problems/10. Named Entity Recognition Baseline.srt 4KB
  179. 2. Beginner's Corner Working with Word Vectors/8. Using pretrained vectors later in the course.srt 4KB
  180. 3. Review of Language Modeling and Neural Networks/10. Review Section Summary.srt 4KB
  181. 3. Review of Language Modeling and Neural Networks/1. Review Section Intro.srt 4KB
  182. 7. Using Neural Networks to Solve NLP Problems/8. Named Entity Recognition (NER).srt 4KB
  183. 11. Appendix FAQ/3. How to Uncompress a .tar.gz file.srt 4KB
  184. 3. Review of Language Modeling and Neural Networks/7. Neural Network Bigram Model in Code.srt 4KB
  185. 1. Outline, Review, and Logistical Things/2. How to Succeed in this Course.srt 4KB
  186. 1. Outline, Review, and Logistical Things/5. Preprocessed Wikipedia Data.srt 4KB
  187. 9. Theano and Tensorflow Basics Review/2. (Review) Theano Neural Network in Code.srt 4KB
  188. 4. Word Embeddings and Word2Vec/1. Return of the Bigram.srt 4KB
  189. 11. Appendix FAQ/1. What is the Appendix.srt 4KB
  190. 5. Word Embeddings using GloVe/12. Visualizing country analogies with t-SNE.srt 4KB
  191. 4. Word Embeddings and Word2Vec/12. Word2Vec Tensorflow in Code.srt 4KB
  192. 11. Appendix FAQ/2. How to install wp2txt or WikiExtractor.py.srt 3KB
  193. 5. Word Embeddings using GloVe/7. Recap of ways to train GloVe.srt 3KB
  194. 5. Word Embeddings using GloVe/13. Hyperparameter Challenge.srt 3KB
  195. 10. Legacy Word2vec Lectures/2. (Legacy) Using pre-trained word embeddings.srt 3KB
  196. 7. Using Neural Networks to Solve NLP Problems/13. Hyperparameter Challenge II.srt 3KB
  197. 5. Word Embeddings using GloVe/9. GloVe in Code - Alternating Least Squares.srt 3KB
  198. 4. Word Embeddings and Word2Vec/7. Why do I have 2 word embedding matrices and what do I do with them.srt 3KB
  199. 5. Word Embeddings using GloVe/1. GloVe Section Introduction.srt 3KB
  200. 5. Word Embeddings using GloVe/10. GloVe in Code - Theano Gradient Descent.srt 3KB
  201. 7. Using Neural Networks to Solve NLP Problems/9. Comparing NER and POS tagging.srt 3KB
  202. 7. Using Neural Networks to Solve NLP Problems/12. Named Entity Recognition RNN in Tensorflow.srt 2KB
  203. 1. Outline, Review, and Logistical Things/4. Where to get the code data for this course.srt 2KB
  204. 7. Using Neural Networks to Solve NLP Problems/11. Named Entity Recognition RNN in Theano.srt 2KB
  205. [FreeCourseWorld.Com].url 54B
  206. [DesireCourse.Net].url 51B
  207. [CourseClub.Me].url 48B