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Natural Language Processing - Probability Models in Python
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Natural Language Processing - Probability Models in Python
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文件列表
Chapter 3 Spam Detection/006. Spam Detection in Python.mp4
56.2 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
31.1 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
13.3 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
4.7 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.9781836201854_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
22.0 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.9781836201854_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.9781836201854_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.9781836201854_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.9781836201854_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.9781836201854_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.9781836201854_Code/CNN_Text_Classification_Packt.ipynb
3.6 kB
z.9781836201854_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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