Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Three Best Practices for Unilever’s Global Analytics Initiatives
    This article from Morgan Vawter, Global Vice...
Getting Machine Learning Projects from Idea to Execution
 Originally published in Harvard Business Review Machine learning might...
Eric Siegel on Bloomberg Businessweek
  Listen to Eric Siegel, former Columbia University Professor,...
Effective Machine Learning Needs Leadership — Not AI Hype
 Originally published in BigThink, Feb 12, 2024.  Excerpted from The...
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Presently, text mining is in a loosely organized set of competing technologies with no clear dominance among them. This book chapter organizes text analytics methods as seven complementary practice areas, showing how to select amongst them for your objectives.

We can relate these technologies to seven different practice areas in text mining that are covered in the chapters in this book. In summary, this book is strongest in the practice area of document classification, solid in concept extraction and document clustering, reasonably useful on web mining, light on information extraction and natural
language processing, and almost silent on the (most popular) practice area of search and information retrieval.

Download your Free Book Chapter on Text Mining here

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