[UdemyCourseDownloader] Mining Data from Text Torrent Download

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Torrent Info
Name:	[UdemyCourseDownloader] Mining Data from Text
Usenet:	Downloads Anonymously to Unlimited data Access! Get Usenet Free Trial
Hash:	D55ED727B512E6FDD2271008D8216557E759BD45
Category:	Other
Peers:	Seeds: 1 & Leechers: 2
Size:	388.61 MB
Stream:	Watch Full HD Movies @ LimeMovies
Date:	2 July 2019

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This is verified, clean and high quality torrent (0) \| Fake (0) \| Password (0) \| Low quality (0) \| Virus (0)

Torrent Files Size: 388.61 MB
[UdemyCourseDownloader] Mining Data from Text Exercise Files mining-data-text.zip - 112.38 MB udemycoursedownloader.com.url - 132 bytes 1.Course Overview 01.Course Overview.en.srt - 2.65 KB 01.Course Overview.mp4 - 3.15 MB 2.Modeling Text Using Natural Language Processing 02.Module Overview.en.srt - 2.14 KB 02.Module Overview.mp4 - 1.94 MB 03.Prerequisites and Course Outline .en.srt - 1.94 KB 03.Prerequisites and Course Outline .mp4 - 1.45 MB 04.Mining Data from Text.en.srt - 3.12 KB 04.Mining Data from Text.mp4 - 2.72 MB 05.Numeric Representations of Text - One Hot Encoding.en.srt - 7.47 KB 05.Numeric Representations of Text - One Hot Encoding.mp4 - 7.19 MB 06.Numeric Representations of Text - Frequency Based Encodings.en.srt - 8.21 KB 06.Numeric Representations of Text - Frequency Based Encodings.mp4 - 6.96 MB 07.Numeric Representations of Text - Prediction Based Embeddings.en.srt - 5.4 KB 07.Numeric Representations of Text - Prediction Based Embeddings.mp4 - 4.82 MB 08.Feature Hashing.en.srt - 5.48 KB 08.Feature Hashing.mp4 - 5.02 MB 09.Bag of Words - Bag of N Grams.en.srt - 3.84 KB 09.Bag of Words - Bag of N Grams.mp4 - 3.52 MB 10.Install and Setup.en.srt - 4.35 KB 10.Install and Setup.mp4 - 4.87 MB 11.Frequency Based Representation Using Bag of Words and Bag of N Grams Model.en.srt - 11.45 KB 11.Frequency Based Representation Using Bag of Words and Bag of N Grams Model.mp4 - 13.97 MB 12.Representing Documents Using TFIDF Scores and Feature Hashes.en.srt - 9.94 KB 12.Representing Documents Using TFIDF Scores and Feature Hashes.mp4 - 12.61 MB 13.Module Summary.en.srt - 2.5 KB 13.Module Summary.mp4 - 2.19 MB 3.Building Classification Models Using Text Data 14.Module Overview.en.srt - 2 KB 14.Module Overview.mp4 - 1.78 MB 15.Naive Bayes Classifier.en.srt - 7.3 KB 15.Naive Bayes Classifier.mp4 - 5.9 MB 16.Sentiment Analysis Using the Naive Bayes Classifier.en.srt - 11.15 KB 16.Sentiment Analysis Using the Naive Bayes Classifier.mp4 - 14.14 MB 17.scikit-learn Pipelines to Build Features .en.srt - 8.11 KB 17.scikit-learn Pipelines to Build Features .mp4 - 10.4 MB 18.Multiclass Classification.en.srt - 7.65 KB 18.Multiclass Classification.mp4 - 9.91 MB 19.Module Summary.en.srt - 1.94 KB 19.Module Summary.mp4 - 1.59 MB 4.Understanding Topic Modeling 20.Module Overview.en.srt - 2.68 KB 20.Module Overview.mp4 - 2.32 MB 21.Topic Modeling.en.srt - 11.87 KB 21.Topic Modeling.mp4 - 10.29 MB 22.Topic Modeling Algorithms.en.srt - 8.99 KB 22.Topic Modeling Algorithms.mp4 - 9.39 MB 23.Module Summary.en.srt - 2.59 KB 23.Module Summary.mp4 - 1.95 MB 5.Implementing Topic Modeling 24.Module Overview.en.srt - 2.1 KB 24.Module Overview.mp4 - 1.87 MB 25.Latent Dirichlet Allocation - Topic Modeling with the Newspaper Headlines Dataset.en.srt - 9.93 KB 25.Latent Dirichlet Allocation - Topic Modeling with the Newspaper Headlines Dataset.mp4 - 12.53 MB 26.Visualizing Topic Assignments Using Manifold Learning to Reduce Dimensions.en.srt - 9.14 KB 26.Visualizing Topic Assignments Using Manifold Learning to Reduce Dimensions.mp4 - 11.65 MB 27.Latent Dirichlet Allocation - Topic Modeling with the DBPedia Dataset.en.srt - 11.13 KB 27.Latent Dirichlet Allocation - Topic Modeling with the DBPedia Dataset.mp4 - 15.41 MB 28.Visualizing Topics Using Manifold Learning to Reduce Dimensions .en.srt - 11.59 KB 28.Visualizing Topics Using Manifold Learning to Reduce Dimensions .mp4 - 18.18 MB 29.Interactive Topic Model Visualization Using PyLDAVis.en.srt - 4.51 KB 29.Interactive Topic Model Visualization Using PyLDAVis.mp4 - 7.01 MB 30.Non-negative Matrix Factorization - Topic Modeling with the DBPedia Dataset.en.srt - 6.97 KB 30.Non-negative Matrix Factorization - Topic Modeling with the DBPedia Dataset.mp4 - 9.77 MB 31.Interactive Topic Visualization Using Bokeh.en.srt - 6.08 KB 31.Interactive Topic Visualization Using Bokeh.mp4 - 10.27 MB 32.Latent Semantic Indexing - Preprocessing Text.en.srt - 9.18 KB 32.Latent Semantic Indexing - Preprocessing Text.mp4 - 13.32 MB 33.Concept Modeling Using LSI.en.srt - 7.56 KB 33.Concept Modeling Using LSI.mp4 - 10.78 MB 34.Module Summary.en.srt - 2.11 KB 34.Module Summary.mp4 - 1.8 MB 6.Understanding and Implementing Keyword Extraction 35.Module Overview.en.srt - 2.05 KB 35.Module Overview.mp4 - 1.88 MB 36.Understanding RAKE for Keyword Extraction.en.srt - 7.07 KB 36.Understanding RAKE for Keyword Extraction.mp4 - 6.2 MB 37.Keyword Extraction Using RAKE.en.srt - 11.69 KB 37.Keyword Extraction Using RAKE.mp4 - 15.22 MB 38.Summary and Further Study.en.srt - 2.64 KB 38.Summary and Further Study.mp4 - 2.03 MB Udemy Course downloader.txt - 94 bytes

Torrent Files

Size: 388.61 MB

[UdemyCourseDownloader] Mining Data from Text

Exercise Files

mining-data-text.zip -

112.38 MB

udemycoursedownloader.com.url -

132 bytes

1.Course Overview

01.Course Overview.en.srt -

2.65 KB

01.Course Overview.mp4 -

3.15 MB

2.Modeling Text Using Natural Language Processing

02.Module Overview.en.srt -

2.14 KB

02.Module Overview.mp4 -

1.94 MB

03.Prerequisites and Course Outline .en.srt -

1.94 KB

03.Prerequisites and Course Outline .mp4 -

1.45 MB

04.Mining Data from Text.en.srt -

3.12 KB

04.Mining Data from Text.mp4 -

2.72 MB

05.Numeric Representations of Text - One Hot Encoding.en.srt -

7.47 KB

05.Numeric Representations of Text - One Hot Encoding.mp4 -

7.19 MB

06.Numeric Representations of Text - Frequency Based Encodings.en.srt -

8.21 KB

06.Numeric Representations of Text - Frequency Based Encodings.mp4 -

6.96 MB

07.Numeric Representations of Text - Prediction Based Embeddings.en.srt -

5.4 KB

07.Numeric Representations of Text - Prediction Based Embeddings.mp4 -

4.82 MB

08.Feature Hashing.en.srt -

5.48 KB

08.Feature Hashing.mp4 -

5.02 MB

09.Bag of Words - Bag of N Grams.en.srt -

3.84 KB

09.Bag of Words - Bag of N Grams.mp4 -

3.52 MB

10.Install and Setup.en.srt -

4.35 KB

10.Install and Setup.mp4 -

4.87 MB

11.Frequency Based Representation Using Bag of Words and Bag of N Grams Model.en.srt -

11.45 KB

11.Frequency Based Representation Using Bag of Words and Bag of N Grams Model.mp4 -

13.97 MB

12.Representing Documents Using TFIDF Scores and Feature Hashes.en.srt -

9.94 KB

12.Representing Documents Using TFIDF Scores and Feature Hashes.mp4 -

12.61 MB

13.Module Summary.en.srt -

2.5 KB

13.Module Summary.mp4 -

2.19 MB

3.Building Classification Models Using Text Data

14.Module Overview.en.srt -

2 KB

14.Module Overview.mp4 -

1.78 MB

15.Naive Bayes Classifier.en.srt -

7.3 KB

15.Naive Bayes Classifier.mp4 -

5.9 MB

16.Sentiment Analysis Using the Naive Bayes Classifier.en.srt -

11.15 KB

16.Sentiment Analysis Using the Naive Bayes Classifier.mp4 -

14.14 MB

17.scikit-learn Pipelines to Build Features .en.srt -

8.11 KB

17.scikit-learn Pipelines to Build Features .mp4 -

10.4 MB

18.Multiclass Classification.en.srt -

7.65 KB

18.Multiclass Classification.mp4 -

9.91 MB

19.Module Summary.en.srt -

1.94 KB

19.Module Summary.mp4 -

1.59 MB

4.Understanding Topic Modeling

20.Module Overview.en.srt -

2.68 KB

20.Module Overview.mp4 -

2.32 MB

21.Topic Modeling.en.srt -

11.87 KB

21.Topic Modeling.mp4 -

10.29 MB

22.Topic Modeling Algorithms.en.srt -

8.99 KB

22.Topic Modeling Algorithms.mp4 -

9.39 MB

23.Module Summary.en.srt -

2.59 KB

23.Module Summary.mp4 -

1.95 MB

5.Implementing Topic Modeling

24.Module Overview.en.srt -

2.1 KB

24.Module Overview.mp4 -

1.87 MB

25.Latent Dirichlet Allocation - Topic Modeling with the Newspaper Headlines Dataset.en.srt -

9.93 KB

25.Latent Dirichlet Allocation - Topic Modeling with the Newspaper Headlines Dataset.mp4 -

12.53 MB

26.Visualizing Topic Assignments Using Manifold Learning to Reduce Dimensions.en.srt -

9.14 KB

26.Visualizing Topic Assignments Using Manifold Learning to Reduce Dimensions.mp4 -

11.65 MB

27.Latent Dirichlet Allocation - Topic Modeling with the DBPedia Dataset.en.srt -

11.13 KB

27.Latent Dirichlet Allocation - Topic Modeling with the DBPedia Dataset.mp4 -

15.41 MB

28.Visualizing Topics Using Manifold Learning to Reduce Dimensions .en.srt -

11.59 KB

28.Visualizing Topics Using Manifold Learning to Reduce Dimensions .mp4 -

18.18 MB

29.Interactive Topic Model Visualization Using PyLDAVis.en.srt -

4.51 KB

29.Interactive Topic Model Visualization Using PyLDAVis.mp4 -

7.01 MB

30.Non-negative Matrix Factorization - Topic Modeling with the DBPedia Dataset.en.srt -

6.97 KB

30.Non-negative Matrix Factorization - Topic Modeling with the DBPedia Dataset.mp4 -

9.77 MB

31.Interactive Topic Visualization Using Bokeh.en.srt -

6.08 KB

31.Interactive Topic Visualization Using Bokeh.mp4 -

10.27 MB

32.Latent Semantic Indexing - Preprocessing Text.en.srt -

9.18 KB

32.Latent Semantic Indexing - Preprocessing Text.mp4 -

13.32 MB

33.Concept Modeling Using LSI.en.srt -

7.56 KB

33.Concept Modeling Using LSI.mp4 -

10.78 MB

34.Module Summary.en.srt -

2.11 KB

34.Module Summary.mp4 -

1.8 MB

6.Understanding and Implementing Keyword Extraction

35.Module Overview.en.srt -

2.05 KB

35.Module Overview.mp4 -

1.88 MB

36.Understanding RAKE for Keyword Extraction.en.srt -

7.07 KB

36.Understanding RAKE for Keyword Extraction.mp4 -

6.2 MB

37.Keyword Extraction Using RAKE.en.srt -

11.69 KB

37.Keyword Extraction Using RAKE.mp4 -

15.22 MB

38.Summary and Further Study.en.srt -

2.64 KB

38.Summary and Further Study.mp4 -

2.03 MB

Udemy Course downloader.txt -

94 bytes

Please note that this page does not hosts or makes available any of the listed filenames. You cannot download any of those files from here.
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