589689.xyz

[] Udemy - Machine Learning Natural Language Processing in Python (V2)

  • 收录时间:2023-07-22 08:11:12
  • 文件大小:7GB
  • 下载次数:1
  • 最近下载:2023-07-22 08:11:12
  • 磁力链接:
立即下载 复制链接

文件列表

  1. 18. Recurrent Neural Networks/9. Parts-of-Speech (POS) Tagging in Tensorflow.mp4 145MB
  2. 3. Vector Models and Text Preprocessing/14. TF-IDF (Code).mp4 125MB
  3. 16. Feedforward Artificial Neural Networks/13. CBOW in Tensorflow (Advanced).mp4 118MB
  4. 21. Effective Learning Strategies for Machine Learning FAQ/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 108MB
  5. 9. Spam Detection/6. Spam Detection in Python.mp4 108MB
  6. 7. Cipher Decryption (Advanced)/4. Genetic Algorithms.mp4 105MB
  7. 3. Vector Models and Text Preprocessing/10. Count Vectorizer (Code).mp4 102MB
  8. 6. Article Spinner (Intermediate)/4. Article Spinner in Python (pt 1).mp4 96MB
  9. 16. Feedforward Artificial Neural Networks/4. Activation Functions.mp4 89MB
  10. 17. Convolutional Neural Networks/6. CNN Architecture.mp4 89MB
  11. 11. Text Summarization/8. TextRank in Python (Advanced).mp4 82MB
  12. 18. Recurrent Neural Networks/6. GRU and LSTM (pt 1).mp4 82MB
  13. 13. Latent Semantic Analysis (Latent Semantic Indexing)/2. SVD (Singular Value Decomposition) Intuition.mp4 82MB
  14. 15. The Neuron/4. Text Classification in Tensorflow.mp4 82MB
  15. 17. Convolutional Neural Networks/2. What is Convolution.mp4 80MB
  16. 3. Vector Models and Text Preprocessing/16. How to Build TF-IDF From Scratch.mp4 80MB
  17. 21. Effective Learning Strategies for Machine Learning FAQ/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 80MB
  18. 11. Text Summarization/4. Text Summarization in Python.mp4 78MB
  19. 6. Article Spinner (Intermediate)/5. Article Spinner in Python (pt 2).mp4 75MB
  20. 17. Convolutional Neural Networks/5. Convolution on Color Images.mp4 75MB
  21. 3. Vector Models and Text Preprocessing/9. Stemming and Lemmatization Demo.mp4 75MB
  22. 3. Vector Models and Text Preprocessing/6. Tokenization.mp4 74MB
  23. 1. Introduction/1. Introduction and Outline.mp4 73MB
  24. 12. Topic Modeling/6. Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.mp4 72MB
  25. 5. Markov Models (Intermediate)/8. Building a Text Classifier (Code pt 2).mp4 72MB
  26. 20. Extra Help With Python Coding for Beginners FAQ/1. How to Code by Yourself (part 1).mp4 72MB
  27. 20. Extra Help With Python Coding for Beginners FAQ/3. Proof that using Jupyter Notebook is the same as not using it.mp4 69MB
  28. 15. The Neuron/2. Fitting a Line.mp4 69MB
  29. 3. Vector Models and Text Preprocessing/18. Neural Word Embeddings Demo.mp4 67MB
  30. 7. Cipher Decryption (Advanced)/3. Language Models (Review).mp4 66MB
  31. 2. Getting Set Up/2. How to use Github & Extra Coding Tips (Optional).mp4 64MB
  32. 10. Sentiment Analysis/2. Logistic Regression Intuition (pt 1).mp4 64MB
  33. 10. Sentiment Analysis/6. Sentiment Analysis in Python (pt 1).mp4 63MB
  34. 5. Markov Models (Intermediate)/11. Language Model (Code pt 1).mp4 63MB
  35. 9. Spam Detection/4. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).mp4 60MB
  36. 12. Topic Modeling/5. Latent Dirichlet Allocation (LDA) - Intuition (Advanced).mp4 60MB
  37. 3. Vector Models and Text Preprocessing/12. TF-IDF (Theory).mp4 59MB
  38. 3. Vector Models and Text Preprocessing/8. Stemming and Lemmatization.mp4 58MB
  39. 5. Markov Models (Intermediate)/7. Building a Text Classifier (Code pt 1).mp4 58MB
  40. 13. Latent Semantic Analysis (Latent Semantic Indexing)/4. Latent Semantic Analysis Latent Semantic Indexing in Python.mp4 58MB
  41. 3. Vector Models and Text Preprocessing/5. Count Vectorizer (Theory).mp4 57MB
  42. 18. Recurrent Neural Networks/5. RNNs Paying Attention to Shapes.mp4 57MB
  43. 16. Feedforward Artificial Neural Networks/3. The Geometrical Picture.mp4 57MB
  44. 3. Vector Models and Text Preprocessing/21. How To Do NLP In Other Languages.mp4 56MB
  45. 12. Topic Modeling/2. Latent Dirichlet Allocation (LDA) - Essentials.mp4 55MB
  46. 9. Spam Detection/5. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).mp4 54MB
  47. 19. Setting Up Your Environment FAQ/2. Anaconda Environment Setup.mp4 53MB
  48. 12. Topic Modeling/7. Non-Negative Matrix Factorization (NMF) Intuition.mp4 52MB
  49. 5. Markov Models (Intermediate)/12. Language Model (Code pt 2).mp4 52MB
  50. 10. Sentiment Analysis/7. Sentiment Analysis in Python (pt 2).mp4 52MB
  51. 15. The Neuron/6. How does a model learn.mp4 52MB
  52. 9. Spam Detection/2. Naive Bayes Intuition.mp4 51MB
  53. 19. Setting Up Your Environment FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 51MB
  54. 18. Recurrent Neural Networks/7. GRU and LSTM (pt 2).mp4 50MB
  55. 16. Feedforward Artificial Neural Networks/8. Text Preprocessing Code Preparation.mp4 50MB
  56. 11. Text Summarization/6. TextRank - How It Really Works (Advanced).mp4 49MB
  57. 20. Extra Help With Python Coding for Beginners FAQ/2. How to Code by Yourself (part 2).mp4 49MB
  58. 3. Vector Models and Text Preprocessing/3. What is a Vector.mp4 49MB
  59. 3. Vector Models and Text Preprocessing/15. Word-to-Index Mapping.mp4 48MB
  60. 16. Feedforward Artificial Neural Networks/2. Forward Propagation.mp4 47MB
  61. 11. Text Summarization/5. TextRank Intuition.mp4 46MB
  62. 18. Recurrent Neural Networks/8. RNN for Text Classification in Tensorflow.mp4 46MB
  63. 5. Markov Models (Intermediate)/3. The Markov Model.mp4 46MB
  64. 3. Vector Models and Text Preprocessing/17. Neural Word Embeddings.mp4 46MB
  65. 15. The Neuron/5. The Neuron.mp4 45MB
  66. 11. Text Summarization/9. Text Summarization in Python - The Easy Way (Beginner).mp4 45MB
  67. 3. Vector Models and Text Preprocessing/11. Vector Similarity.mp4 45MB
  68. 5. Markov Models (Intermediate)/9. Language Model (Theory).mp4 45MB
  69. 16. Feedforward Artificial Neural Networks/5. Multiclass Classification.mp4 44MB
  70. 2. Getting Set Up/1. Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4 44MB
  71. 10. Sentiment Analysis/1. Sentiment Analysis - Problem Description.mp4 43MB
  72. 16. Feedforward Artificial Neural Networks/10. Embeddings.mp4 42MB
  73. 18. Recurrent Neural Networks/4. RNN Code Preparation.mp4 42MB
  74. 17. Convolutional Neural Networks/8. Convolutional Neural Network for NLP in Tensorflow.mp4 42MB
  75. 6. Article Spinner (Intermediate)/1. Article Spinning - Problem Description.mp4 42MB
  76. 2. Getting Set Up/4. How to Succeed in This Course.mp4 41MB
  77. 18. Recurrent Neural Networks/3. Simple RNN Elman Unit (pt 2).mp4 41MB
  78. 7. Cipher Decryption (Advanced)/10. Code pt 5.mp4 41MB
  79. 18. Recurrent Neural Networks/2. Simple RNN Elman Unit (pt 1).mp4 41MB
  80. 17. Convolutional Neural Networks/7. CNNs for Text.mp4 40MB
  81. 22. Appendix FAQ Finale/2. BONUS.mp4 40MB
  82. 10. Sentiment Analysis/4. Logistic Regression Training and Interpretation (pt 3).mp4 40MB
  83. 7. Cipher Decryption (Advanced)/11. Code pt 6.mp4 39MB
  84. 7. Cipher Decryption (Advanced)/7. Code pt 2.mp4 39MB
  85. 21. Effective Learning Strategies for Machine Learning FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39MB
  86. 16. Feedforward Artificial Neural Networks/1. ANN - Section Introduction.mp4 39MB
  87. 16. Feedforward Artificial Neural Networks/15. Aside How to Choose Hyperparameters (Optional).mp4 38MB
  88. 16. Feedforward Artificial Neural Networks/7. Text Classification ANN in Tensorflow.mp4 36MB
  89. 12. Topic Modeling/8. Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.mp4 36MB
  90. 13. Latent Semantic Analysis (Latent Semantic Indexing)/3. LSA LSI Applying SVD to NLP.mp4 34MB
  91. 5. Markov Models (Intermediate)/4. Probability Smoothing and Log-Probabilities.mp4 34MB
  92. 15. The Neuron/3. Classification Code Preparation.mp4 33MB
  93. 5. Markov Models (Intermediate)/2. The Markov Property.mp4 32MB
  94. 18. Recurrent Neural Networks/10. Named Entity Recognition (NER) in Tensorflow.mp4 32MB
  95. 9. Spam Detection/1. Spam Detection - Problem Description.mp4 31MB
  96. 16. Feedforward Artificial Neural Networks/9. Text Preprocessing in Tensorflow.mp4 31MB
  97. 17. Convolutional Neural Networks/4. What is Convolution (Weight Sharing).mp4 30MB
  98. 8. Machine Learning Models (Introduction)/1. Machine Learning Models (Introduction).mp4 30MB
  99. 7. Cipher Decryption (Advanced)/8. Code pt 3.mp4 30MB
  100. 5. Markov Models (Intermediate)/6. Building a Text Classifier (Exercise Prompt).mp4 29MB
  101. 13. Latent Semantic Analysis (Latent Semantic Indexing)/5. LSA LSI Exercises.mp4 29MB
  102. 5. Markov Models (Intermediate)/5. Building a Text Classifier (Theory).mp4 29MB
  103. 5. Markov Models (Intermediate)/10. Language Model (Exercise Prompt).mp4 29MB
  104. 3. Vector Models and Text Preprocessing/2. Basic Definitions for NLP.mp4 28MB
  105. 6. Article Spinner (Intermediate)/6. Case Study Article Spinning Gone Wrong.mp4 28MB
  106. 3. Vector Models and Text Preprocessing/22. Suggestion Box.mp4 27MB
  107. 4. Probabilistic Models (Introduction)/1. Probabilistic Models (Introduction).mp4 27MB
  108. 1. Introduction/2. Are You Beginner, Intermediate, or Advanced All are OK!.mp4 27MB
  109. 7. Cipher Decryption (Advanced)/1. Section Introduction.mp4 26MB
  110. 11. Text Summarization/2. Text Summarization Using Vectors.mp4 26MB
  111. 11. Text Summarization/1. Text Summarization Section Introduction.mp4 26MB
  112. 7. Cipher Decryption (Advanced)/9. Code pt 4.mp4 26MB
  113. 17. Convolutional Neural Networks/1. CNN - Section Introduction.mp4 26MB
  114. 6. Article Spinner (Intermediate)/3. Article Spinner Exercise Prompt.mp4 25MB
  115. 17. Convolutional Neural Networks/3. What is Convolution (Pattern Matching).mp4 25MB
  116. 14. Deep Learning (Introduction)/1. Deep Learning Introduction (Intermediate-Advanced).mp4 25MB
  117. 7. Cipher Decryption (Advanced)/13. Section Conclusion.mp4 24MB
  118. 10. Sentiment Analysis/3. Multiclass Logistic Regression (pt 2).mp4 24MB
  119. 3. Vector Models and Text Preprocessing/7. Stopwords.mp4 23MB
  120. 19. Setting Up Your Environment FAQ/1. Pre-Installation Check.mp4 23MB
  121. 2. Getting Set Up/5. Temporary 403 Errors.mp4 22MB
  122. 13. Latent Semantic Analysis (Latent Semantic Indexing)/1. LSA LSI Section Introduction.mp4 21MB
  123. 18. Recurrent Neural Networks/1. RNN - Section Introduction.mp4 21MB
  124. 3. Vector Models and Text Preprocessing/19. Vector Models & Text Preprocessing Summary.mp4 21MB
  125. 7. Cipher Decryption (Advanced)/5. Code Preparation.mp4 21MB
  126. 16. Feedforward Artificial Neural Networks/6. ANN Code Preparation.mp4 20MB
  127. 11. Text Summarization/10. Text Summarization Section Summary.mp4 20MB
  128. 21. Effective Learning Strategies for Machine Learning FAQ/1. How to Succeed in this Course (Long Version).mp4 18MB
  129. 2. Getting Set Up/3. Where to get the code, notebooks, and data.mp4 18MB
  130. 3. Vector Models and Text Preprocessing/1. Vector Models & Text Preprocessing Intro.mp4 18MB
  131. 7. Cipher Decryption (Advanced)/2. Ciphers.mp4 17MB
  132. 12. Topic Modeling/1. Topic Modeling Section Introduction.mp4 17MB
  133. 10. Sentiment Analysis/5. Sentiment Analysis - Exercise Prompt.mp4 17MB
  134. 22. Appendix FAQ Finale/1. What is the Appendix.mp4 16MB
  135. 7. Cipher Decryption (Advanced)/6. Code pt 1.mp4 16MB
  136. 6. Article Spinner (Intermediate)/2. Article Spinning - N-Gram Approach.mp4 16MB
  137. 16. Feedforward Artificial Neural Networks/11. CBOW (Advanced).mp4 16MB
  138. 5. Markov Models (Intermediate)/13. Markov Models Section Summary.mp4 16MB
  139. 7. Cipher Decryption (Advanced)/12. Cipher Decryption - Additional Discussion.mp4 15MB
  140. 18. Recurrent Neural Networks/11. Exercise Return to CNNs (Advanced).mp4 15MB
  141. 12. Topic Modeling/3. LDA - Code Preparation.mp4 15MB
  142. 3. Vector Models and Text Preprocessing/4. Bag of Words.mp4 14MB
  143. 3. Vector Models and Text Preprocessing/13. (Interactive) Recommender Exercise Prompt.mp4 13MB
  144. 5. Markov Models (Intermediate)/1. Markov Models Section Introduction.mp4 13MB
  145. 15. The Neuron/1. The Neuron - Section Introduction.mp4 11MB
  146. 15. The Neuron/7. The Neuron - Section Summary.mp4 10MB
  147. 12. Topic Modeling/9. Topic Modeling Section Summary.mp4 10MB
  148. 18. Recurrent Neural Networks/12. RNN - Section Summary.mp4 9MB
  149. 12. Topic Modeling/4. LDA - Maybe Useful Picture (Optional).mp4 9MB
  150. 9. Spam Detection/3. Spam Detection - Exercise Prompt.mp4 9MB
  151. 17. Convolutional Neural Networks/9. CNN - Section Summary.mp4 8MB
  152. 11. Text Summarization/3. Text Summarization Exercise Prompt.mp4 8MB
  153. 16. Feedforward Artificial Neural Networks/14. ANN - Section Summary.mp4 8MB
  154. 11. Text Summarization/7. TextRank Exercise Prompt (Advanced).mp4 7MB
  155. 3. Vector Models and Text Preprocessing/20. Text Summarization Preview.mp4 6MB
  156. 16. Feedforward Artificial Neural Networks/12. CBOW Exercise Prompt.mp4 5MB
  157. 21. Effective Learning Strategies for Machine Learning FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 32KB
  158. 7. Cipher Decryption (Advanced)/4. Genetic Algorithms.srt 29KB
  159. 17. Convolutional Neural Networks/6. CNN Architecture.srt 29KB
  160. 3. Vector Models and Text Preprocessing/14. TF-IDF (Code).srt 25KB
  161. 21. Effective Learning Strategies for Machine Learning FAQ/4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt 24KB
  162. 18. Recurrent Neural Networks/6. GRU and LSTM (pt 1).srt 23KB
  163. 16. Feedforward Artificial Neural Networks/4. Activation Functions.srt 23KB
  164. 20. Extra Help With Python Coding for Beginners FAQ/1. How to Code by Yourself (part 1).srt 23KB
  165. 18. Recurrent Neural Networks/9. Parts-of-Speech (POS) Tagging in Tensorflow.srt 23KB
  166. 10. Sentiment Analysis/2. Logistic Regression Intuition (pt 1).srt 23KB
  167. 17. Convolutional Neural Networks/5. Convolution on Color Images.srt 21KB
  168. 6. Article Spinner (Intermediate)/4. Article Spinner in Python (pt 1).srt 21KB
  169. 17. Convolutional Neural Networks/2. What is Convolution.srt 21KB
  170. 7. Cipher Decryption (Advanced)/3. Language Models (Review).srt 21KB
  171. 16. Feedforward Artificial Neural Networks/13. CBOW in Tensorflow (Advanced).srt 20KB
  172. 12. Topic Modeling/5. Latent Dirichlet Allocation (LDA) - Intuition (Advanced).srt 20KB
  173. 19. Setting Up Your Environment FAQ/2. Anaconda Environment Setup.srt 20KB
  174. 3. Vector Models and Text Preprocessing/6. Tokenization.srt 20KB
  175. 9. Spam Detection/6. Spam Detection in Python.srt 19KB
  176. 3. Vector Models and Text Preprocessing/5. Count Vectorizer (Theory).srt 19KB
  177. 3. Vector Models and Text Preprocessing/10. Count Vectorizer (Code).srt 19KB
  178. 3. Vector Models and Text Preprocessing/16. How to Build TF-IDF From Scratch.srt 19KB
  179. 15. The Neuron/2. Fitting a Line.srt 18KB
  180. 3. Vector Models and Text Preprocessing/12. TF-IDF (Theory).srt 18KB
  181. 11. Text Summarization/8. TextRank in Python (Advanced).srt 17KB
  182. 9. Spam Detection/4. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).srt 17KB
  183. 21. Effective Learning Strategies for Machine Learning FAQ/3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt 17KB
  184. 5. Markov Models (Intermediate)/3. The Markov Model.srt 16KB
  185. 3. Vector Models and Text Preprocessing/8. Stemming and Lemmatization.srt 16KB
  186. 2. Getting Set Up/2. How to use Github & Extra Coding Tips (Optional).srt 16KB
  187. 1. Introduction/1. Introduction and Outline.srt 15KB
  188. 13. Latent Semantic Analysis (Latent Semantic Indexing)/2. SVD (Singular Value Decomposition) Intuition.srt 15KB
  189. 9. Spam Detection/2. Naive Bayes Intuition.srt 15KB
  190. 12. Topic Modeling/2. Latent Dirichlet Allocation (LDA) - Essentials.srt 15KB
  191. 3. Vector Models and Text Preprocessing/11. Vector Similarity.srt 15KB
  192. 18. Recurrent Neural Networks/7. GRU and LSTM (pt 2).srt 15KB
  193. 11. Text Summarization/4. Text Summarization in Python.srt 15KB
  194. 16. Feedforward Artificial Neural Networks/8. Text Preprocessing Code Preparation.srt 15KB
  195. 3. Vector Models and Text Preprocessing/3. What is a Vector.srt 15KB
  196. 3. Vector Models and Text Preprocessing/15. Word-to-Index Mapping.srt 15KB
  197. 19. Setting Up Your Environment FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 15KB
  198. 3. Vector Models and Text Preprocessing/21. How To Do NLP In Other Languages.srt 15KB
  199. 21. Effective Learning Strategies for Machine Learning FAQ/1. How to Succeed in this Course (Long Version).srt 15KB
  200. 9. Spam Detection/5. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).srt 14KB
  201. 15. The Neuron/6. How does a model learn.srt 14KB
  202. 20. Extra Help With Python Coding for Beginners FAQ/3. Proof that using Jupyter Notebook is the same as not using it.srt 14KB
  203. 3. Vector Models and Text Preprocessing/9. Stemming and Lemmatization Demo.srt 14KB
  204. 5. Markov Models (Intermediate)/8. Building a Text Classifier (Code pt 2).srt 14KB
  205. 12. Topic Modeling/7. Non-Negative Matrix Factorization (NMF) Intuition.srt 14KB
  206. 11. Text Summarization/6. TextRank - How It Really Works (Advanced).srt 14KB
  207. 3. Vector Models and Text Preprocessing/17. Neural Word Embeddings.srt 13KB
  208. 20. Extra Help With Python Coding for Beginners FAQ/2. How to Code by Yourself (part 2).srt 13KB
  209. 5. Markov Models (Intermediate)/9. Language Model (Theory).srt 13KB
  210. 12. Topic Modeling/6. Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.srt 13KB
  211. 5. Markov Models (Intermediate)/11. Language Model (Code pt 1).srt 13KB
  212. 2. Getting Set Up/4. How to Succeed in This Course.srt 13KB
  213. 18. Recurrent Neural Networks/3. Simple RNN Elman Unit (pt 2).srt 13KB
  214. 3. Vector Models and Text Preprocessing/18. Neural Word Embeddings Demo.srt 13KB
  215. 15. The Neuron/5. The Neuron.srt 13KB
  216. 16. Feedforward Artificial Neural Networks/10. Embeddings.srt 13KB
  217. 16. Feedforward Artificial Neural Networks/2. Forward Propagation.srt 13KB
  218. 18. Recurrent Neural Networks/4. RNN Code Preparation.srt 13KB
  219. 6. Article Spinner (Intermediate)/5. Article Spinner in Python (pt 2).srt 12KB
  220. 2. Getting Set Up/1. Get Your Hands Dirty, Practical Coding Experience, Data Links.srt 12KB
  221. 5. Markov Models (Intermediate)/7. Building a Text Classifier (Code pt 1).srt 12KB
  222. 16. Feedforward Artificial Neural Networks/3. The Geometrical Picture.srt 12KB
  223. 15. The Neuron/4. Text Classification in Tensorflow.srt 12KB
  224. 10. Sentiment Analysis/6. Sentiment Analysis in Python (pt 1).srt 12KB
  225. 18. Recurrent Neural Networks/2. Simple RNN Elman Unit (pt 1).srt 12KB
  226. 16. Feedforward Artificial Neural Networks/5. Multiclass Classification.srt 11KB
  227. 5. Markov Models (Intermediate)/12. Language Model (Code pt 2).srt 11KB
  228. 11. Text Summarization/5. TextRank Intuition.srt 11KB
  229. 10. Sentiment Analysis/4. Logistic Regression Training and Interpretation (pt 3).srt 11KB
  230. 6. Article Spinner (Intermediate)/1. Article Spinning - Problem Description.srt 11KB
  231. 5. Markov Models (Intermediate)/4. Probability Smoothing and Log-Probabilities.srt 10KB
  232. 13. Latent Semantic Analysis (Latent Semantic Indexing)/3. LSA LSI Applying SVD to NLP.srt 10KB
  233. 18. Recurrent Neural Networks/5. RNNs Paying Attention to Shapes.srt 10KB
  234. 13. Latent Semantic Analysis (Latent Semantic Indexing)/4. Latent Semantic Analysis Latent Semantic Indexing in Python.srt 10KB
  235. 10. Sentiment Analysis/1. Sentiment Analysis - Problem Description.srt 10KB
  236. 17. Convolutional Neural Networks/7. CNNs for Text.srt 10KB
  237. 10. Sentiment Analysis/7. Sentiment Analysis in Python (pt 2).srt 10KB
  238. 15. The Neuron/3. Classification Code Preparation.srt 10KB
  239. 5. Markov Models (Intermediate)/2. The Markov Property.srt 9KB
  240. 5. Markov Models (Intermediate)/5. Building a Text Classifier (Theory).srt 9KB
  241. 16. Feedforward Artificial Neural Networks/1. ANN - Section Introduction.srt 9KB
  242. 7. Cipher Decryption (Advanced)/7. Code pt 2.srt 9KB
  243. 5. Markov Models (Intermediate)/10. Language Model (Exercise Prompt).srt 9KB
  244. 7. Cipher Decryption (Advanced)/10. Code pt 5.srt 9KB
  245. 5. Markov Models (Intermediate)/6. Building a Text Classifier (Exercise Prompt).srt 9KB
  246. 9. Spam Detection/1. Spam Detection - Problem Description.srt 9KB
  247. 16. Feedforward Artificial Neural Networks/15. Aside How to Choose Hyperparameters (Optional).srt 9KB
  248. 10. Sentiment Analysis/3. Multiclass Logistic Regression (pt 2).srt 8KB
  249. 7. Cipher Decryption (Advanced)/13. Section Conclusion.srt 8KB
  250. 17. Convolutional Neural Networks/4. What is Convolution (Weight Sharing).srt 8KB
  251. 22. Appendix FAQ Finale/2. BONUS.srt 8KB
  252. 8. Machine Learning Models (Introduction)/1. Machine Learning Models (Introduction).srt 8KB
  253. 11. Text Summarization/9. Text Summarization in Python - The Easy Way (Beginner).srt 8KB
  254. 6. Article Spinner (Intermediate)/3. Article Spinner Exercise Prompt.srt 8KB
  255. 6. Article Spinner (Intermediate)/6. Case Study Article Spinning Gone Wrong.srt 8KB
  256. 11. Text Summarization/1. Text Summarization Section Introduction.srt 8KB
  257. 13. Latent Semantic Analysis (Latent Semantic Indexing)/5. LSA LSI Exercises.srt 7KB
  258. 11. Text Summarization/2. Text Summarization Using Vectors.srt 7KB
  259. 7. Cipher Decryption (Advanced)/11. Code pt 6.srt 7KB
  260. 1. Introduction/2. Are You Beginner, Intermediate, or Advanced All are OK!.srt 7KB
  261. 17. Convolutional Neural Networks/3. What is Convolution (Pattern Matching).srt 7KB
  262. 14. Deep Learning (Introduction)/1. Deep Learning Introduction (Intermediate-Advanced).srt 7KB
  263. 7. Cipher Decryption (Advanced)/5. Code Preparation.srt 7KB
  264. 7. Cipher Decryption (Advanced)/1. Section Introduction.srt 7KB
  265. 3. Vector Models and Text Preprocessing/2. Basic Definitions for NLP.srt 7KB
  266. 19. Setting Up Your Environment FAQ/1. Pre-Installation Check.srt 7KB
  267. 18. Recurrent Neural Networks/1. RNN - Section Introduction.srt 6KB
  268. 3. Vector Models and Text Preprocessing/7. Stopwords.srt 6KB
  269. 16. Feedforward Artificial Neural Networks/9. Text Preprocessing in Tensorflow.srt 6KB
  270. 4. Probabilistic Models (Introduction)/1. Probabilistic Models (Introduction).srt 6KB
  271. 7. Cipher Decryption (Advanced)/8. Code pt 3.srt 6KB
  272. 18. Recurrent Neural Networks/10. Named Entity Recognition (NER) in Tensorflow.srt 6KB
  273. 16. Feedforward Artificial Neural Networks/6. ANN Code Preparation.srt 6KB
  274. 17. Convolutional Neural Networks/1. CNN - Section Introduction.srt 6KB
  275. 18. Recurrent Neural Networks/8. RNN for Text Classification in Tensorflow.srt 6KB
  276. 16. Feedforward Artificial Neural Networks/11. CBOW (Advanced).srt 5KB
  277. 6. Article Spinner (Intermediate)/2. Article Spinning - N-Gram Approach.srt 5KB
  278. 13. Latent Semantic Analysis (Latent Semantic Indexing)/1. LSA LSI Section Introduction.srt 5KB
  279. 10. Sentiment Analysis/5. Sentiment Analysis - Exercise Prompt.srt 5KB
  280. 16. Feedforward Artificial Neural Networks/7. Text Classification ANN in Tensorflow.srt 5KB
  281. 17. Convolutional Neural Networks/8. Convolutional Neural Network for NLP in Tensorflow.srt 5KB
  282. 3. Vector Models and Text Preprocessing/1. Vector Models & Text Preprocessing Intro.srt 5KB
  283. 12. Topic Modeling/3. LDA - Code Preparation.srt 5KB
  284. 12. Topic Modeling/8. Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.srt 5KB
  285. 7. Cipher Decryption (Advanced)/9. Code pt 4.srt 5KB
  286. 7. Cipher Decryption (Advanced)/2. Ciphers.srt 5KB
  287. 3. Vector Models and Text Preprocessing/19. Vector Models & Text Preprocessing Summary.srt 5KB
  288. 3. Vector Models and Text Preprocessing/22. Suggestion Box.srt 5KB
  289. 11. Text Summarization/10. Text Summarization Section Summary.srt 4KB
  290. 2. Getting Set Up/3. Where to get the code, notebooks, and data.srt 4KB
  291. 7. Cipher Decryption (Advanced)/6. Code pt 1.srt 4KB
  292. 18. Recurrent Neural Networks/11. Exercise Return to CNNs (Advanced).srt 4KB
  293. 12. Topic Modeling/1. Topic Modeling Section Introduction.srt 4KB
  294. 7. Cipher Decryption (Advanced)/12. Cipher Decryption - Additional Discussion.srt 4KB
  295. 5. Markov Models (Intermediate)/13. Markov Models Section Summary.srt 4KB
  296. 22. Appendix FAQ Finale/1. What is the Appendix.srt 4KB
  297. 2. Getting Set Up/5. Temporary 403 Errors.srt 4KB
  298. 5. Markov Models (Intermediate)/1. Markov Models Section Introduction.srt 3KB
  299. 3. Vector Models and Text Preprocessing/13. (Interactive) Recommender Exercise Prompt.srt 3KB
  300. 3. Vector Models and Text Preprocessing/4. Bag of Words.srt 3KB
  301. 15. The Neuron/1. The Neuron - Section Introduction.srt 3KB
  302. 9. Spam Detection/3. Spam Detection - Exercise Prompt.srt 3KB
  303. 12. Topic Modeling/4. LDA - Maybe Useful Picture (Optional).srt 3KB
  304. 18. Recurrent Neural Networks/12. RNN - Section Summary.srt 2KB
  305. 11. Text Summarization/3. Text Summarization Exercise Prompt.srt 2KB
  306. 15. The Neuron/7. The Neuron - Section Summary.srt 2KB
  307. 12. Topic Modeling/9. Topic Modeling Section Summary.srt 2KB
  308. 16. Feedforward Artificial Neural Networks/14. ANN - Section Summary.srt 2KB
  309. 11. Text Summarization/7. TextRank Exercise Prompt (Advanced).srt 2KB
  310. 3. Vector Models and Text Preprocessing/20. Text Summarization Preview.srt 2KB
  311. 17. Convolutional Neural Networks/9. CNN - Section Summary.srt 2KB
  312. 16. Feedforward Artificial Neural Networks/12. CBOW Exercise Prompt.srt 970B
  313. 2. Getting Set Up/1.1 Data Links.html 157B
  314. 2. Getting Set Up/3.2 Data Links.html 157B
  315. 2. Getting Set Up/1.2 Github Link.html 139B
  316. 2. Getting Set Up/3.3 Github Link.html 139B
  317. 2. Getting Set Up/3.1 Code Link.html 125B
  318. 0. Websites you may like/[CourseClub.Me].url 122B
  319. 10. Sentiment Analysis/0. Websites you may like/[CourseClub.Me].url 122B
  320. 10. Sentiment Analysis/[CourseClub.Me].url 122B
  321. [CourseClub.Me].url 122B
  322. 0. Websites you may like/[GigaCourse.Com].url 49B
  323. 10. Sentiment Analysis/0. Websites you may like/[GigaCourse.Com].url 49B
  324. 10. Sentiment Analysis/[GigaCourse.Com].url 49B
  325. [GigaCourse.Com].url 49B