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

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视频 2023-3-2 10:32 2024-4-26 17:23 146 6.59 GB 153
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GigaCourse Com Udemy - Machine Learning Natural Language Processing in Python V2

文件列表
  1. 01 - Introduction/001 Introduction and Outline.mp472.97MB
  2. 01 - Introduction/002 Are You Beginner, Intermediate, or Advanced All are OK!.mp426.66MB
  3. 02 - Getting Set Up/001 Get Your Hands Dirty, Practical Coding Experience, Data Links.mp443.56MB
  4. 02 - Getting Set Up/002 How to use Github & Extra Coding Tips (Optional).mp463.88MB
  5. 03 - Vector Models and Text Preprocessing/001 Vector Models & Text Preprocessing Intro.mp417.52MB
  6. 03 - Vector Models and Text Preprocessing/002 Basic Definitions for NLP.mp428.36MB
  7. 03 - Vector Models and Text Preprocessing/003 What is a Vector.mp448.93MB
  8. 03 - Vector Models and Text Preprocessing/004 Bag of Words.mp413.85MB
  9. 03 - Vector Models and Text Preprocessing/005 Count Vectorizer (Theory).mp457.43MB
  10. 03 - Vector Models and Text Preprocessing/006 Tokenization.mp473.51MB
  11. 03 - Vector Models and Text Preprocessing/007 Stopwords.mp423.44MB
  12. 03 - Vector Models and Text Preprocessing/008 Stemming and Lemmatization.mp457.92MB
  13. 03 - Vector Models and Text Preprocessing/009 Stemming and Lemmatization Demo.mp474.84MB
  14. 03 - Vector Models and Text Preprocessing/010 Count Vectorizer (Code).mp4101.98MB
  15. 03 - Vector Models and Text Preprocessing/011 Vector Similarity.mp445.11MB
  16. 03 - Vector Models and Text Preprocessing/012 TF-IDF (Theory).mp458.57MB
  17. 03 - Vector Models and Text Preprocessing/013 (Interactive) Recommender Exercise Prompt.mp413.38MB
  18. 03 - Vector Models and Text Preprocessing/014 TF-IDF (Code).mp4124.92MB
  19. 03 - Vector Models and Text Preprocessing/015 Word-to-Index Mapping.mp447.58MB
  20. 03 - Vector Models and Text Preprocessing/016 How to Build TF-IDF From Scratch.mp479.79MB
  21. 03 - Vector Models and Text Preprocessing/017 Neural Word Embeddings.mp445.54MB
  22. 03 - Vector Models and Text Preprocessing/018 Neural Word Embeddings Demo.mp466.84MB
  23. 03 - Vector Models and Text Preprocessing/019 Vector Models & Text Preprocessing Summary.mp420.85MB
  24. 03 - Vector Models and Text Preprocessing/020 Text Summarization Preview.mp46.28MB
  25. 03 - Vector Models and Text Preprocessing/021 How To Do NLP In Other Languages.mp455.96MB
  26. 03 - Vector Models and Text Preprocessing/022 Suggestion Box.mp427.16MB
  27. 04 - Probabilistic Models (Introduction)/001 Probabilistic Models (Introduction).mp426.91MB
  28. 05 - Markov Models (Intermediate)/001 Markov Models Section Introduction.mp413.09MB
  29. 05 - Markov Models (Intermediate)/002 The Markov Property.mp432.25MB
  30. 05 - Markov Models (Intermediate)/003 The Markov Model.mp445.84MB
  31. 05 - Markov Models (Intermediate)/004 Probability Smoothing and Log-Probabilities.mp434.06MB
  32. 05 - Markov Models (Intermediate)/005 Building a Text Classifier (Theory).mp428.92MB
  33. 05 - Markov Models (Intermediate)/006 Building a Text Classifier (Exercise Prompt).mp429.36MB
  34. 05 - Markov Models (Intermediate)/007 Building a Text Classifier (Code pt 1).mp457.68MB
  35. 05 - Markov Models (Intermediate)/008 Building a Text Classifier (Code pt 2).mp472.22MB
  36. 05 - Markov Models (Intermediate)/009 Language Model (Theory).mp444.96MB
  37. 05 - Markov Models (Intermediate)/010 Language Model (Exercise Prompt).mp428.8MB
  38. 05 - Markov Models (Intermediate)/011 Language Model (Code pt 1).mp462.83MB
  39. 05 - Markov Models (Intermediate)/012 Language Model (Code pt 2).mp452.43MB
  40. 05 - Markov Models (Intermediate)/013 Markov Models Section Summary.mp415.56MB
  41. 06 - Article Spinner (Intermediate)/001 Article Spinning - Problem Description.mp441.92MB
  42. 06 - Article Spinner (Intermediate)/002 Article Spinning - N-Gram Approach.mp415.92MB
  43. 06 - Article Spinner (Intermediate)/003 Article Spinner Exercise Prompt.mp424.62MB
  44. 06 - Article Spinner (Intermediate)/004 Article Spinner in Python (pt 1).mp495.89MB
  45. 06 - Article Spinner (Intermediate)/005 Article Spinner in Python (pt 2).mp475.37MB
  46. 06 - Article Spinner (Intermediate)/006 Case Study Article Spinning Gone Wrong.mp428.23MB
  47. 07 - Cipher Decryption (Advanced)/001 Section Introduction.mp426.32MB
  48. 07 - Cipher Decryption (Advanced)/002 Ciphers.mp417.21MB
  49. 07 - Cipher Decryption (Advanced)/003 Language Models (Review).mp465.53MB
  50. 07 - Cipher Decryption (Advanced)/004 Genetic Algorithms.mp4105.16MB
  51. 07 - Cipher Decryption (Advanced)/005 Code Preparation.mp420.63MB
  52. 07 - Cipher Decryption (Advanced)/006 Code pt 1.mp415.98MB
  53. 07 - Cipher Decryption (Advanced)/007 Code pt 2.mp439.13MB
  54. 07 - Cipher Decryption (Advanced)/008 Code pt 3.mp429.54MB
  55. 07 - Cipher Decryption (Advanced)/009 Code pt 4.mp425.62MB
  56. 07 - Cipher Decryption (Advanced)/010 Code pt 5.mp440.96MB
  57. 07 - Cipher Decryption (Advanced)/011 Code pt 6.mp439.4MB
  58. 07 - Cipher Decryption (Advanced)/012 Cipher Decryption - Additional Discussion.mp414.7MB
  59. 07 - Cipher Decryption (Advanced)/013 Section Conclusion.mp424.24MB
  60. 08 - Machine Learning Models (Introduction)/001 Machine Learning Models (Introduction).mp429.6MB
  61. 09 - Spam Detection/001 Spam Detection - Problem Description.mp431.33MB
  62. 09 - Spam Detection/002 Naive Bayes Intuition.mp451.33MB
  63. 09 - Spam Detection/003 Spam Detection - Exercise Prompt.mp48.73MB
  64. 09 - Spam Detection/004 Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).mp460.21MB
  65. 09 - Spam Detection/005 Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).mp453.97MB
  66. 09 - Spam Detection/006 Spam Detection in Python.mp4107.6MB
  67. 10 - Sentiment Analysis/001 Sentiment Analysis - Problem Description.mp442.7MB
  68. 10 - Sentiment Analysis/002 Logistic Regression Intuition (pt 1).mp463.57MB
  69. 10 - Sentiment Analysis/003 Multiclass Logistic Regression (pt 2).mp423.61MB
  70. 10 - Sentiment Analysis/004 Logistic Regression Training and Interpretation (pt 3).mp439.63MB
  71. 10 - Sentiment Analysis/005 Sentiment Analysis - Exercise Prompt.mp416.55MB
  72. 10 - Sentiment Analysis/006 Sentiment Analysis in Python (pt 1).mp463.15MB
  73. 10 - Sentiment Analysis/007 Sentiment Analysis in Python (pt 2).mp451.96MB
  74. 11 - Text Summarization/001 Text Summarization Section Introduction.mp425.75MB
  75. 11 - Text Summarization/002 Text Summarization Using Vectors.mp425.77MB
  76. 11 - Text Summarization/003 Text Summarization Exercise Prompt.mp48.1MB
  77. 11 - Text Summarization/004 Text Summarization in Python.mp478.15MB
  78. 11 - Text Summarization/005 TextRank Intuition.mp445.92MB
  79. 11 - Text Summarization/006 TextRank - How It Really Works (Advanced).mp449.31MB
  80. 11 - Text Summarization/007 TextRank Exercise Prompt (Advanced).mp47.47MB
  81. 11 - Text Summarization/008 TextRank in Python (Advanced).mp482.3MB
  82. 11 - Text Summarization/009 Text Summarization in Python - The Easy Way (Beginner).mp445.17MB
  83. 11 - Text Summarization/010 Text Summarization Section Summary.mp420.1MB
  84. 12 - Topic Modeling/001 Topic Modeling Section Introduction.mp417.04MB
  85. 12 - Topic Modeling/002 Latent Dirichlet Allocation (LDA) - Essentials.mp455.18MB
  86. 12 - Topic Modeling/003 LDA - Code Preparation.mp414.51MB
  87. 12 - Topic Modeling/004 LDA - Maybe Useful Picture (Optional).mp48.98MB
  88. 12 - Topic Modeling/005 Latent Dirichlet Allocation (LDA) - Intuition (Advanced).mp460.18MB
  89. 12 - Topic Modeling/006 Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.mp472.38MB
  90. 12 - Topic Modeling/007 Non-Negative Matrix Factorization (NMF) Intuition.mp452.48MB
  91. 12 - Topic Modeling/008 Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.mp436.03MB
  92. 12 - Topic Modeling/009 Topic Modeling Section Summary.mp49.81MB
  93. 13 - Latent Semantic Analysis (Latent Semantic Indexing)/001 LSA LSI Section Introduction.mp420.95MB
  94. 13 - Latent Semantic Analysis (Latent Semantic Indexing)/002 SVD (Singular Value Decomposition) Intuition.mp481.84MB
  95. 13 - Latent Semantic Analysis (Latent Semantic Indexing)/003 LSA LSI Applying SVD to NLP.mp434.42MB
  96. 13 - Latent Semantic Analysis (Latent Semantic Indexing)/004 Latent Semantic Analysis Latent Semantic Indexing in Python.mp457.55MB
  97. 13 - Latent Semantic Analysis (Latent Semantic Indexing)/005 LSA LSI Exercises.mp429.05MB
  98. 14 - Deep Learning (Introduction)/001 Deep Learning Introduction (Intermediate-Advanced).mp424.52MB
  99. 15 - The Neuron/001 The Neuron - Section Introduction.mp411.01MB
  100. 15 - The Neuron/002 Fitting a Line.mp468.61MB
  101. 15 - The Neuron/003 Classification Code Preparation.mp432.88MB
  102. 15 - The Neuron/004 Text Classification in Tensorflow.mp481.66MB
  103. 15 - The Neuron/005 The Neuron.mp445.25MB
  104. 15 - The Neuron/006 How does a model learn.mp451.58MB
  105. 15 - The Neuron/007 The Neuron - Section Summary.mp410.31MB
  106. 16 - Feedforward Artificial Neural Networks/001 ANN - Section Introduction.mp438.63MB
  107. 16 - Feedforward Artificial Neural Networks/002 Forward Propagation.mp446.72MB
  108. 16 - Feedforward Artificial Neural Networks/003 The Geometrical Picture.mp456.53MB
  109. 16 - Feedforward Artificial Neural Networks/004 Activation Functions.mp489.31MB
  110. 16 - Feedforward Artificial Neural Networks/005 Multiclass Classification.mp444.41MB
  111. 16 - Feedforward Artificial Neural Networks/006 ANN Code Preparation.mp420.14MB
  112. 16 - Feedforward Artificial Neural Networks/007 Text Classification ANN in Tensorflow.mp436.12MB
  113. 16 - Feedforward Artificial Neural Networks/008 Text Preprocessing Code Preparation.mp449.99MB
  114. 16 - Feedforward Artificial Neural Networks/009 Text Preprocessing in Tensorflow.mp430.93MB
  115. 16 - Feedforward Artificial Neural Networks/010 Embeddings.mp442.28MB
  116. 16 - Feedforward Artificial Neural Networks/011 CBOW (Advanced).mp415.77MB
  117. 16 - Feedforward Artificial Neural Networks/012 CBOW Exercise Prompt.mp45.02MB
  118. 16 - Feedforward Artificial Neural Networks/013 CBOW in Tensorflow (Advanced).mp4117.55MB
  119. 16 - Feedforward Artificial Neural Networks/014 ANN - Section Summary.mp47.6MB
  120. 16 - Feedforward Artificial Neural Networks/015 Aside How to Choose Hyperparameters (Optional).mp438.07MB
  121. 17 - Convolutional Neural Networks/001 CNN - Section Introduction.mp425.62MB
  122. 17 - Convolutional Neural Networks/002 What is Convolution.mp479.86MB
  123. 17 - Convolutional Neural Networks/003 What is Convolution (Pattern Matching).mp424.62MB
  124. 17 - Convolutional Neural Networks/004 What is Convolution (Weight Sharing).mp428.83MB
  125. 17 - Convolutional Neural Networks/005 Convolution on Color Images.mp475.19MB
  126. 17 - Convolutional Neural Networks/006 CNN Architecture.mp489.28MB
  127. 17 - Convolutional Neural Networks/007 CNNs for Text.mp440.48MB
  128. 17 - Convolutional Neural Networks/008 Convolutional Neural Network for NLP in Tensorflow.mp442.04MB
  129. 17 - Convolutional Neural Networks/009 CNN - Section Summary.mp48.19MB
  130. 18 - Recurrent Neural Networks/001 RNN - Section Introduction.mp420.9MB
  131. 18 - Recurrent Neural Networks/002 Simple RNN Elman Unit (pt 1).mp440.83MB
  132. 18 - Recurrent Neural Networks/003 Simple RNN Elman Unit (pt 2).mp441.18MB
  133. 18 - Recurrent Neural Networks/004 RNN Code Preparation.mp442.14MB
  134. 18 - Recurrent Neural Networks/005 RNNs Paying Attention to Shapes.mp457.17MB
  135. 18 - Recurrent Neural Networks/006 GRU and LSTM (pt 1).mp482.25MB
  136. 18 - Recurrent Neural Networks/007 GRU and LSTM (pt 2).mp450.34MB
  137. 18 - Recurrent Neural Networks/008 RNN for Text Classification in Tensorflow.mp445.91MB
  138. 18 - Recurrent Neural Networks/009 Parts-of-Speech (POS) Tagging in Tensorflow.mp4145.1MB
  139. 18 - Recurrent Neural Networks/010 Named Entity Recognition (NER) in Tensorflow.mp431.54MB
  140. 18 - Recurrent Neural Networks/011 Exercise Return to CNNs (Advanced).mp414.55MB
  141. 18 - Recurrent Neural Networks/012 RNN - Section Summary.mp49.09MB
  142. 19 - Setting Up Your Environment FAQ/001 Anaconda Environment Setup.mp452.63MB
  143. 19 - Setting Up Your Environment FAQ/002 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp450.9MB
  144. 20 - Extra Help With Python Coding for Beginners FAQ/001 Where to get the code, notebooks, and data.mp417.72MB
  145. 20 - Extra Help With Python Coding for Beginners FAQ/002 How to Code by Yourself (part 1).mp471.86MB
  146. 20 - Extra Help With Python Coding for Beginners FAQ/003 How to Code by Yourself (part 2).mp449.15MB
  147. 20 - Extra Help With Python Coding for Beginners FAQ/004 Proof that using Jupyter Notebook is the same as not using it.mp469.42MB
  148. 21 - Effective Learning Strategies for Machine Learning FAQ/001 How to Succeed in this Course (Long Version).mp417.87MB
  149. 21 - Effective Learning Strategies for Machine Learning FAQ/002 Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp438.95MB
  150. 21 - Effective Learning Strategies for Machine Learning FAQ/003 Machine Learning and AI Prerequisite Roadmap (pt 1).mp479.67MB
  151. 21 - Effective Learning Strategies for Machine Learning FAQ/004 Machine Learning and AI Prerequisite Roadmap (pt 2).mp4108.15MB
  152. 22 - Appendix FAQ Finale/001 What is the Appendix.mp416.39MB
  153. 22 - Appendix FAQ Finale/002 BONUS.mp439.88MB
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