Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
The Quant’s Dilemma: Subjectivity In Predictive AI’s Value
 Originally published in Forbes This is the third of a...
To Deploy Predictive AI, You Must Navigate These Tradeoffs
 Originally published in Forbes This is the second of a...
Data Analytics in Higher Education
 Universities confront many of the same marketing challenges as...
How Generative AI Helps Predictive AI
 Originally published in Forbes, August 21, 2024 This is 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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