Natural Language Processing - Probability Models in Python

Creation Time	Aug. 16, 2024, 12:16 a.m.
Last Access Time	Nov. 17, 2024, 4:37 p.m.
File Size	788.8 MB
Keywords	Natural Language Probability Models Processing - Python in
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Total Files	90
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Chapter 3 Spam Detection/006. Spam Detection in Python.mp4 53.6 MB
Chapter 5 Text Summarization/008. TextRank in Python (Advanced).mp4 39.0 MB
Chapter 5 Text Summarization/004. Text Summarization in Python.mp4 37.3 MB
Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/002. SVD (Singular Value Decomposition) Intuition.mp4 36.9 MB
Chapter 6 Topic Modeling/006. Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.mp4 34.9 MB
Chapter 4 Sentiment Analysis/002. Logistic Regression Intuition (pt 1).mp4 34.1 MB
Chapter 6 Topic Modeling/005. Latent Dirichlet Allocation (LDA) - Intuition (Advanced).mp4 31.6 MB
Chapter 4 Sentiment Analysis/006. Sentiment Analysis in Python (pt 1).mp4 29.6 MB
Chapter 3 Spam Detection/004. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).mp4 29.2 MB
Chapter 6 Topic Modeling/002. Latent Dirichlet Allocation (LDA) - Essentials.mp4 26.7 MB
Chapter 3 Spam Detection/005. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).mp4 26.7 MB
Chapter 3 Spam Detection/002. Naive Bayes Intuition.mp4 26.2 MB
Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/004. Latent Semantic Analysis Latent Semantic Indexing in Python.mp4 26.2 MB
Chapter 6 Topic Modeling/007. Non-Negative Matrix Factorization (NMF) Intuition.mp4 24.9 MB
Chapter 5 Text Summarization/006. TextRank - How It Really Works (Advanced).mp4 24.7 MB
Chapter 4 Sentiment Analysis/007. Sentiment Analysis in Python (pt 2).mp4 23.7 MB
Chapter 5 Text Summarization/005. TextRank Intuition.mp4 21.3 MB
Chapter 5 Text Summarization/009. Text Summarization in Python - The Easy Way (Beginner).mp4 20.9 MB
Chapter 4 Sentiment Analysis/004. Logistic Regression Training and Interpretation.mp4 20.4 MB
Chapter 4 Sentiment Analysis/001. Sentiment Analysis - Problem Description.mp4 19.9 MB
Chapter 1 Welcome/001. Introduction and Outline.mp4 19.0 MB
Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/003. LSA LSI Applying SVD to NLP.mp4 17.5 MB
Chapter 6 Topic Modeling/008. Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.mp4 16.6 MB
Chapter 3 Spam Detection/001. Spam Detection - Problem Description.mp4 15.1 MB
Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/005. LSA LSI Exercises.mp4 14.3 MB
Chapter 4 Sentiment Analysis/003. Multiclass Logistic Regression (pt 2).mp4 12.8 MB
Chapter 5 Text Summarization/002. Text Summarization Using Vectors.mp4 12.8 MB
Chapter 5 Text Summarization/001. Text Summarization Section Introduction.mp4 12.6 MB
Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/001. LSA LSI Section Introduction.mp4 9.8 MB
Chapter 5 Text Summarization/010. Text Summarization Section Summary.mp4 9.1 MB
Chapter 4 Sentiment Analysis/005. Sentiment Analysis - Exercise Prompt.mp4 8.5 MB
Chapter 6 Topic Modeling/001. Topic Modeling Section Introduction.mp4 8.4 MB
Chapter 6 Topic Modeling/003. LDA - Code Preparation.mp4 7.6 MB
Chapter 2 Getting Set Up/001. Where To Get the Code.mp4 7.0 MB
Chapter 2 Getting Set Up/002. How To Succeed in This Course.mp4 6.3 MB
Chapter 6 Topic Modeling/009. Topic Modeling Section Summary.mp4 4.4 MB
Chapter 3 Spam Detection/003. Spam Detection - Exercise Prompt.mp4 4.3 MB
Chapter 6 Topic Modeling/004. LDA - Maybe Useful Picture (Optional).mp4 4.1 MB
Chapter 5 Text Summarization/003. Text Summarization Exercise Prompt.mp4 3.9 MB
Chapter 5 Text Summarization/007. TextRank Exercise Prompt (Advanced).mp4 3.4 MB
Chapter 1 Welcome/002. Special Offer.mp4 3.2 MB
z.9781836201854_Code/TF2_Classification_Packt.ipynb 31.1 KB
Chapter 4 Sentiment Analysis/002. Logistic Regression Intuition (pt 1).en.srt 24.0 KB
Chapter 6 Topic Modeling/005. Latent Dirichlet Allocation (LDA) - Intuition (Advanced).en.srt 21.5 KB
Chapter 3 Spam Detection/006. Spam Detection in Python.en.srt 20.5 KB
Chapter 5 Text Summarization/008. TextRank in Python (Advanced).en.srt 18.4 KB
Chapter 3 Spam Detection/004. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).en.srt 17.9 KB
Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/002. SVD (Singular Value Decomposition) Intuition.en.srt 16.8 KB
Chapter 6 Topic Modeling/002. Latent Dirichlet Allocation (LDA) - Essentials.en.srt 16.3 KB
Chapter 5 Text Summarization/004. Text Summarization in Python.en.srt 16.2 KB
Chapter 3 Spam Detection/002. Naive Bayes Intuition.en.srt 16.1 KB
Chapter 3 Spam Detection/005. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).en.srt 14.9 KB
z.9781836201854_Code/Linear_Regression_Packt.ipynb 14.8 KB
Chapter 6 Topic Modeling/007. Non-Negative Matrix Factorization (NMF) Intuition.en.srt 14.7 KB
Chapter 5 Text Summarization/006. TextRank - How It Really Works (Advanced).en.srt 14.4 KB
Chapter 6 Topic Modeling/006. Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.en.srt 13.7 KB
Chapter 4 Sentiment Analysis/006. Sentiment Analysis in Python (pt 1).en.srt 12.1 KB
Chapter 1 Welcome/001. Introduction and Outline.en.srt 12.0 KB
Chapter 5 Text Summarization/005. TextRank Intuition.en.srt 11.7 KB
Chapter 4 Sentiment Analysis/004. Logistic Regression Training and Interpretation.en.srt 11.4 KB
Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/003. LSA LSI Applying SVD to NLP.en.srt 10.8 KB
Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/004. Latent Semantic Analysis Latent Semantic Indexing in Python.en.srt 10.6 KB
Chapter 4 Sentiment Analysis/001. Sentiment Analysis - Problem Description.en.srt 10.4 KB
Chapter 4 Sentiment Analysis/007. Sentiment Analysis in Python (pt 2).en.srt 9.8 KB
Chapter 3 Spam Detection/001. Spam Detection - Problem Description.en.srt 9.3 KB
Chapter 4 Sentiment Analysis/003. Multiclass Logistic Regression (pt 2).en.srt 8.9 KB
Chapter 5 Text Summarization/009. Text Summarization in Python - The Easy Way (Beginner).en.srt 8.2 KB
Chapter 5 Text Summarization/001. Text Summarization Section Introduction.en.srt 8.0 KB
Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/005. LSA LSI Exercises.en.srt 7.9 KB
z.9781836201854_Code/POS_Tagging_Packt.ipynb 7.9 KB
Chapter 5 Text Summarization/002. Text Summarization Using Vectors.en.srt 7.5 KB
Chapter 4 Sentiment Analysis/005. Sentiment Analysis - Exercise Prompt.en.srt 5.6 KB
Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/001. LSA LSI Section Introduction.en.srt 5.5 KB
z.9781836201854_Code/NER_TF2_Packt.ipynb 5.3 KB
Chapter 6 Topic Modeling/003. LDA - Code Preparation.en.srt 5.2 KB
Chapter 6 Topic Modeling/008. Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.en.srt 5.1 KB
z.9781836201854_Code/CBOW_in_TF2_Packt.ipynb 4.7 KB
Chapter 2 Getting Set Up/002. How To Succeed in This Course.en.srt 4.6 KB
Chapter 5 Text Summarization/010. Text Summarization Section Summary.en.srt 4.6 KB
Chapter 6 Topic Modeling/001. Topic Modeling Section Introduction.en.srt 4.5 KB
z.9781836201854_Code/RNN_Text_Classification_Packt.ipynb 4.2 KB
Chapter 2 Getting Set Up/001. Where To Get the Code.en.srt 4.0 KB
z.9781836201854_Code/CNN_Text_Classification_Packt.ipynb 3.5 KB
z.9781836201854_Code/TF2_ANN_with_TFIDF_Packt.ipynb 3.5 KB
Chapter 3 Spam Detection/003. Spam Detection - Exercise Prompt.en.srt 2.8 KB
Chapter 6 Topic Modeling/004. LDA - Maybe Useful Picture (Optional).en.srt 2.5 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

Natural Language Processing - Probability Models in Python

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