Natural Language Processing - Machine Learning Models in Python

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Natural Language Processing - Machine Learning Models in Python

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收录时间：2024-07-23
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文件列表

  • Chapter 3 Spam Detection/006. Spam Detection in Python.mp4 56.1 MB
  • Chapter 5 Text Summarization/008. TextRank in Python (Advanced).mp4 40.9 MB
  • Chapter 5 Text Summarization/004. Text Summarization in Python.mp4 39.1 MB
  • Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/002. SVD (Singular Value Decomposition) Intuition.mp4 38.7 MB
  • Chapter 6 Topic Modeling/006. Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.mp4 36.6 MB
  • Chapter 4 Sentiment Analysis/002. Logistic Regression Intuition (pt 1).mp4 35.8 MB
  • Chapter 6 Topic Modeling/005. Latent Dirichlet Allocation (LDA) - Intuition (Advanced).mp4 33.1 MB
  • Chapter 4 Sentiment Analysis/006. Sentiment Analysis in Python (pt 1).mp4 31.0 MB
  • Chapter 3 Spam Detection/004. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).mp4 30.6 MB
  • Chapter 6 Topic Modeling/002. Latent Dirichlet Allocation (LDA) - Essentials.mp4 28.0 MB
  • Chapter 3 Spam Detection/005. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).mp4 28.0 MB
  • Chapter 3 Spam Detection/002. Naive Bayes Intuition.mp4 27.5 MB
  • Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/004. Latent Semantic Analysis Latent Semantic Indexing in Python.mp4 27.4 MB
  • Chapter 6 Topic Modeling/007. Non-Negative Matrix Factorization (NMF) Intuition.mp4 26.1 MB
  • Chapter 5 Text Summarization/006. TextRank - How It Really Works (Advanced).mp4 25.9 MB
  • Chapter 4 Sentiment Analysis/007. Sentiment Analysis in Python (pt 2).mp4 24.9 MB
  • Chapter 5 Text Summarization/005. TextRank Intuition.mp4 22.3 MB
  • Chapter 5 Text Summarization/009. Text Summarization in Python - The Easy Way (Beginner).mp4 21.9 MB
  • Chapter 4 Sentiment Analysis/004. Logistic Regression Training and Interpretation.mp4 21.4 MB
  • Chapter 4 Sentiment Analysis/001. Sentiment Analysis - Problem Description.mp4 20.8 MB
  • Chapter 1 Welcome/001. Introduction and Outline.mp4 19.9 MB
  • Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/003. LSA LSI Applying SVD to NLP.mp4 18.3 MB
  • Chapter 6 Topic Modeling/008. Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.mp4 17.4 MB
  • Chapter 3 Spam Detection/001. Spam Detection - Problem Description.mp4 15.8 MB
  • Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/005. LSA LSI Exercises.mp4 15.0 MB
  • Chapter 4 Sentiment Analysis/003. Multiclass Logistic Regression (pt 2).mp4 13.5 MB
  • Chapter 5 Text Summarization/002. Text Summarization Using Vectors.mp4 13.4 MB
  • Chapter 5 Text Summarization/001. Text Summarization Section Introduction.mp4 13.2 MB
  • Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/001. LSA LSI Section Introduction.mp4 10.3 MB
  • Chapter 5 Text Summarization/010. Text Summarization Section Summary.mp4 9.5 MB
  • Chapter 4 Sentiment Analysis/005. Sentiment Analysis - Exercise Prompt.mp4 8.9 MB
  • Chapter 6 Topic Modeling/001. Topic Modeling Section Introduction.mp4 8.8 MB
  • Chapter 6 Topic Modeling/003. LDA - Code Preparation.mp4 7.9 MB
  • Chapter 2 Getting Set Up/001. Where To Get the Code.mp4 7.4 MB
  • Chapter 2 Getting Set Up/002. How To Succeed in This Course.mp4 6.6 MB
  • Chapter 6 Topic Modeling/009. Topic Modeling Section Summary.mp4 4.6 MB
  • Chapter 3 Spam Detection/003. Spam Detection - Exercise Prompt.mp4 4.5 MB
  • Chapter 6 Topic Modeling/004. LDA - Maybe Useful Picture (Optional).mp4 4.3 MB
  • Chapter 5 Text Summarization/003. Text Summarization Exercise Prompt.mp4 4.1 MB
  • Chapter 5 Text Summarization/007. TextRank Exercise Prompt (Advanced).mp4 3.6 MB
  • Chapter 1 Welcome/002. Special Offer.mp4 3.3 MB
  • z.9781836205579_Code/TF2_Classification_Packt.ipynb 31.8 kB
  • Chapter 4 Sentiment Analysis/002. Logistic Regression Intuition (pt 1).en.srt 24.5 kB
  • Chapter 6 Topic Modeling/005. Latent Dirichlet Allocation (LDA) - Intuition (Advanced).en.srt 21.9 kB
  • Chapter 3 Spam Detection/006. Spam Detection in Python.en.srt 21.0 kB
  • Chapter 5 Text Summarization/008. TextRank in Python (Advanced).en.srt 18.9 kB
  • Chapter 3 Spam Detection/004. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).en.srt 18.4 kB
  • Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/002. SVD (Singular Value Decomposition) Intuition.en.srt 17.2 kB
  • Chapter 6 Topic Modeling/002. Latent Dirichlet Allocation (LDA) - Essentials.en.srt 16.6 kB
  • Chapter 5 Text Summarization/004. Text Summarization in Python.en.srt 16.6 kB
  • Chapter 3 Spam Detection/002. Naive Bayes Intuition.en.srt 16.4 kB
  • Chapter 3 Spam Detection/005. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).en.srt 15.3 kB
  • z.9781836205579_Code/Linear_Regression_Packt.ipynb 15.2 kB
  • Chapter 6 Topic Modeling/007. Non-Negative Matrix Factorization (NMF) Intuition.en.srt 15.0 kB
  • Chapter 5 Text Summarization/006. TextRank - How It Really Works (Advanced).en.srt 14.7 kB
  • Chapter 6 Topic Modeling/006. Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.en.srt 14.0 kB
  • Chapter 4 Sentiment Analysis/006. Sentiment Analysis in Python (pt 1).en.srt 12.4 kB
  • Chapter 1 Welcome/001. Introduction and Outline.en.srt 12.3 kB
  • Chapter 5 Text Summarization/005. TextRank Intuition.en.srt 12.0 kB
  • Chapter 4 Sentiment Analysis/004. Logistic Regression Training and Interpretation.en.srt 11.6 kB
  • Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/003. LSA LSI Applying SVD to NLP.en.srt 11.0 kB
  • Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/004. Latent Semantic Analysis Latent Semantic Indexing in Python.en.srt 10.8 kB
  • Chapter 4 Sentiment Analysis/001. Sentiment Analysis - Problem Description.en.srt 10.7 kB
  • Chapter 4 Sentiment Analysis/007. Sentiment Analysis in Python (pt 2).en.srt 10.0 kB
  • Chapter 3 Spam Detection/001. Spam Detection - Problem Description.en.srt 9.5 kB
  • Chapter 4 Sentiment Analysis/003. Multiclass Logistic Regression (pt 2).en.srt 9.1 kB
  • Chapter 5 Text Summarization/009. Text Summarization in Python - The Easy Way (Beginner).en.srt 8.3 kB
  • Chapter 5 Text Summarization/001. Text Summarization Section Introduction.en.srt 8.2 kB
  • Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/005. LSA LSI Exercises.en.srt 8.1 kB
  • z.9781836205579_Code/POS_Tagging_Packt.ipynb 8.1 kB
  • Chapter 5 Text Summarization/002. Text Summarization Using Vectors.en.srt 7.7 kB
  • Chapter 4 Sentiment Analysis/005. Sentiment Analysis - Exercise Prompt.en.srt 5.7 kB
  • Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/001. LSA LSI Section Introduction.en.srt 5.6 kB
  • z.9781836205579_Code/NER_TF2_Packt.ipynb 5.5 kB
  • Chapter 6 Topic Modeling/003. LDA - Code Preparation.en.srt 5.3 kB
  • Chapter 6 Topic Modeling/008. Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.en.srt 5.2 kB
  • z.9781836205579_Code/CBOW_in_TF2_Packt.ipynb 4.8 kB
  • Chapter 2 Getting Set Up/002. How To Succeed in This Course.en.srt 4.8 kB
  • Chapter 5 Text Summarization/010. Text Summarization Section Summary.en.srt 4.7 kB
  • Chapter 6 Topic Modeling/001. Topic Modeling Section Introduction.en.srt 4.6 kB
  • z.9781836205579_Code/RNN_Text_Classification_Packt.ipynb 4.3 kB
  • Chapter 2 Getting Set Up/001. Where To Get the Code.en.srt 4.1 kB
  • z.9781836205579_Code/CNN_Text_Classification_Packt.ipynb 3.6 kB
  • z.9781836205579_Code/TF2_ANN_with_TFIDF_Packt.ipynb 3.6 kB
  • Chapter 3 Spam Detection/003. Spam Detection - Exercise Prompt.en.srt 2.9 kB
  • Chapter 6 Topic Modeling/004. LDA - Maybe Useful Picture (Optional).en.srt 2.6 kB
  • Chapter 5 Text Summarization/003. Text Summarization Exercise Prompt.en.srt 2.4 kB
  • Chapter 6 Topic Modeling/009. Topic Modeling Section Summary.en.srt 2.1 kB
  • Chapter 5 Text Summarization/007. TextRank Exercise Prompt (Advanced).en.srt 1.8 kB
  • Chapter 1 Welcome/002. Special Offer.en.srt 1.7 kB

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