Course Review – Text Mining and Analytics (ChengXiang Zhai, UIUC)

Here is my review of Jun-Jul 2015 Coursera incarnation of Text Mining and Analytics, which is the 4th course in Data Mining specialization. It is ranked 3.5 out of 5, while I passed with 97.5% grade.

Technologies/Material: While Text Retrieval and Search Engines course concentrates on structuring big textual data, this course emphasizes extraction of knowledge from relevant processed sets. Various Natural Language Processing (NLP) techniques are presented such as topic modeling, mixture models, Probabilistic Latent Semantic Analysis (PLSA), Latent Dirichlet Allocation (LDA), entropy-based models. The course concentrates on clustering, text categorization, opinion mining and sentiment analysis, which are the topics on the forefront of NLP.

Instructor/lectures: ChengXiang Zhai is a prominent researcher in Information Retrieval and Natural Language Processing. He worked in the industry as a Research Scientist. Lectures are well structured and are self-contained. It’s easy to follow the lecture slides to reconstruct the material.

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