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Coursera - Text Mining and Analytics (The University of Illinois at Urbana-Champaign)
WEBRip | English | MP4 + PDF Guides | 960 x 540 | AVC ~50 kbps | 29.970 fps
AAC | 128 Kbps | 44.1 KHz | 2 channels | Subs: English (.srt) | 12:07:13 | 1014 MB

Genre: eLearning Video / Data Clustering Algorithms, Probabilistic Models, Sentiment Analysis
This course will cover the major techniques for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision making, with an emphasis on statistical approaches that can be generally applied to arbitrary text data in any natural language with no or minimum human effort.

This course will cover the major techniques for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision making, with an emphasis on statistical approaches that can be generally applied to arbitrary text data in any natural language with no or minimum human effort.
Detailed analysis of text data requires understanding of natural language text, which is known to be a difficult task for computers. However, a number of statistical approaches have been shown to work well for the "shallow" but robust analysis of text data for pattern finding and knowledge discovery. You will learn the basic concepts, principles, and major algorithms in text mining and their potential applications.











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