[UdemyCourseDownloader] Data Science Natural Language Processing (NLP) in Python


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Torrent File Content (125 files)


[UdemyCourseDownloader] Data Science Natural Language Processing (NLP) in Python
    10. Appendix
          2. Windows-Focused Environment Setup 2018.mp4 -
186.47 MB

     udemycoursedownloader.com.url -
132 bytes

    01. Natural Language Processing - What is it used for
          1. Introduction and Outline.mp4 -
2.51 MB

          1. Introduction and Outline.vtt -
7.49 KB

          2. NLP Applications.mp4 -
5.72 MB

          2. NLP Applications.vtt -
14.07 KB

          3. Why is NLP hard.mp4 -
7.13 MB

          3. Why is NLP hard.vtt -
8.31 KB

          4. The Central Message of this Course.mp4 -
3.15 MB

          4. The Central Message of this Course.vtt -
6.36 KB

    02. Course Preparation
          1. How to Succeed in this Course.mp4 -
3.3 MB

          1. How to Succeed in this Course.vtt -
7.14 KB

          2. Where to get the code and data.mp4 -
4.43 MB

          2. Where to get the code and data.vtt -
5.57 KB

          3. Do you need a review of machine learning.mp4 -
13.39 MB

          3. Do you need a review of machine learning.vtt -
6.2 KB

    03. Build your own spam detector
          1. Build your own spam detector - description of data.mp4 -
1.9 MB

          1. Build your own spam detector - description of data.vtt -
4.57 KB

          2. Build your own spam detector using Naive Bayes and AdaBoost - the code.mp4 -
6.54 MB

          2. Build your own spam detector using Naive Bayes and AdaBoost - the code.vtt -
9.98 KB

          3. Key Takeaway from Spam Detection Exercise.mp4 -
30.59 MB

          3. Key Takeaway from Spam Detection Exercise.vtt -
13.32 KB

          4. Naive Bayes Concepts.mp4 -
39.65 MB

          4. Naive Bayes Concepts.vtt -
20.48 KB

          5. AdaBoost Concepts.mp4 -
26.75 MB

          5. AdaBoost Concepts.vtt -
10.95 KB

          6. Other types of features.mp4 -
1.42 MB

          6. Other types of features.vtt -
3.19 KB

          7. Spam Detection FAQ (Remedial #1).mp4 -
10.67 MB

          7. Spam Detection FAQ (Remedial #1).vtt -
20.65 KB

          8. What is a Vector (Remedial #2).mp4 -
9.07 MB

          8. What is a Vector (Remedial #2).vtt -
13.73 KB

          9. SMS Spam Example.mp4 -
5.71 MB

          9. SMS Spam Example.vtt -
13.88 KB

          10. SMS Spam in Code.mp4 -
13.92 MB

          10. SMS Spam in Code.vtt -
19.11 KB

    04. Build your own sentiment analyzer
          1. Description of Sentiment Analyzer.mp4 -
5.06 MB

          1. Description of Sentiment Analyzer.vtt -
7.18 KB

          2. Logistic Regression Review.mp4 -
12.2 MB

          2. Logistic Regression Review.vtt -
16.49 KB

          3. Preprocessing Tokenization.mp4 -
7.73 MB

          3. Preprocessing Tokenization.vtt -
10.12 KB

          4. Preprocessing Tokens to Vectors.mp4 -
10.55 MB

          4. Preprocessing Tokens to Vectors.vtt -
12.68 KB

          5. Sentiment Analysis in Python using Logistic Regression.mp4 -
43.54 MB

          5. Sentiment Analysis in Python using Logistic Regression.vtt -
13.95 KB

          6. Sentiment Analysis Extension.mp4 -
5.16 MB

          6. Sentiment Analysis Extension.vtt -
13.39 KB

          7. How to Improve Sentiment Analysis & FAQ.mp4 -
77.73 MB

          7. How to Improve Sentiment Analysis & FAQ.vtt -
28.56 KB



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