种子简介
种子名称：
[UdemyCourseDownloader] Mining Data from Text
文件类型：
视频
文件数目：
38个文件
文件大小：
276 MB
收录时间：
2019-11-18 00:09
已经下载：
3次
资源热度：
124
最近下载：
2024-12-15 07:38
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种子包含的文件
[UdemyCourseDownloader] Mining Data from Text.torrent
1.Course Overview/01.Course Overview.mp43.15MB
2.Modeling Text Using Natural Language Processing/02.Module Overview.mp41.94MB
2.Modeling Text Using Natural Language Processing/03.Prerequisites and Course Outline .mp41.45MB
2.Modeling Text Using Natural Language Processing/04.Mining Data from Text.mp42.72MB
2.Modeling Text Using Natural Language Processing/05.Numeric Representations of Text - One Hot Encoding.mp47.19MB
2.Modeling Text Using Natural Language Processing/06.Numeric Representations of Text - Frequency Based Encodings.mp46.96MB
2.Modeling Text Using Natural Language Processing/07.Numeric Representations of Text - Prediction Based Embeddings.mp44.82MB
2.Modeling Text Using Natural Language Processing/08.Feature Hashing.mp45.02MB
2.Modeling Text Using Natural Language Processing/09.Bag of Words - Bag of N Grams.mp43.52MB
2.Modeling Text Using Natural Language Processing/10.Install and Setup.mp44.87MB
2.Modeling Text Using Natural Language Processing/11.Frequency Based Representation Using Bag of Words and Bag of N Grams Model.mp413.97MB
2.Modeling Text Using Natural Language Processing/12.Representing Documents Using TFIDF Scores and Feature Hashes.mp412.61MB
2.Modeling Text Using Natural Language Processing/13.Module Summary.mp42.19MB
3.Building Classification Models Using Text Data/14.Module Overview.mp41.78MB
3.Building Classification Models Using Text Data/15.Naive Bayes Classifier.mp45.9MB
3.Building Classification Models Using Text Data/16.Sentiment Analysis Using the Naive Bayes Classifier.mp414.14MB
3.Building Classification Models Using Text Data/17.scikit-learn Pipelines to Build Features .mp410.4MB
3.Building Classification Models Using Text Data/18.Multiclass Classification.mp49.91MB
3.Building Classification Models Using Text Data/19.Module Summary.mp41.59MB
4.Understanding Topic Modeling/20.Module Overview.mp42.32MB
4.Understanding Topic Modeling/21.Topic Modeling.mp410.29MB
4.Understanding Topic Modeling/22.Topic Modeling Algorithms.mp49.39MB
4.Understanding Topic Modeling/23.Module Summary.mp41.95MB
5.Implementing Topic Modeling/24.Module Overview.mp41.87MB
5.Implementing Topic Modeling/25.Latent Dirichlet Allocation - Topic Modeling with the Newspaper Headlines Dataset.mp412.53MB
5.Implementing Topic Modeling/26.Visualizing Topic Assignments Using Manifold Learning to Reduce Dimensions.mp411.65MB
5.Implementing Topic Modeling/27.Latent Dirichlet Allocation - Topic Modeling with the DBPedia Dataset.mp415.41MB
5.Implementing Topic Modeling/28.Visualizing Topics Using Manifold Learning to Reduce Dimensions .mp418.18MB
5.Implementing Topic Modeling/29.Interactive Topic Model Visualization Using PyLDAVis.mp47.01MB
5.Implementing Topic Modeling/30.Non-negative Matrix Factorization - Topic Modeling with the DBPedia Dataset.mp49.77MB
5.Implementing Topic Modeling/31.Interactive Topic Visualization Using Bokeh.mp410.27MB
5.Implementing Topic Modeling/32.Latent Semantic Indexing - Preprocessing Text.mp413.32MB
5.Implementing Topic Modeling/33.Concept Modeling Using LSI.mp410.78MB
5.Implementing Topic Modeling/34.Module Summary.mp41.8MB
6.Understanding and Implementing Keyword Extraction/35.Module Overview.mp41.88MB
6.Understanding and Implementing Keyword Extraction/36.Understanding RAKE for Keyword Extraction.mp46.2MB
6.Understanding and Implementing Keyword Extraction/37.Keyword Extraction Using RAKE.mp415.22MB
6.Understanding and Implementing Keyword Extraction/38.Summary and Further Study.mp42.03MB
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