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Algorithms of the Intelligent Web, Second Edition (Paperback, 2nd edition)
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Algorithms of the Intelligent Web, Second Edition (Paperback, 2nd edition)
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DESCRIPTION There's priceless insight trapped in the flood of data
users leave behind as they interact with web pages and
applications. Those insights can be unlocked by using intelligent
algorithms like the ones that have earned Facebook, Google,
Twitter, and Microsoft a place among the giants of web data pattern
extraction. Improved search, data classification, and other smart
pattern matching techniques can give an enormous advantage to
understanding and interacting with users. Algorithms of the
Intelligent Web, Second Edition has been totally revised and
teaches the most important approaches to algorithmic web data
analysis, enabling readers to create machine learning applications
that crunch, munge, and wrangle data collected from users, web
applications, sensors, and website logs. Key machine learning
concepts are explained and introduced with many code examples in
Python's scikit-learn. The book guides readers through the
underlying machinery and intelligent algorithms to capture, store,
and structure data streams. Readers will explore recommendation
engines from the example of Netflix movie recommendations and dive
into classification via statistical algorithms, neural networks,
and deep learning. They will also consider the ins and outs of
ranking and how to test applications based on intelligent
algorithms. KEY SELLING POINTS Machine learning for newbies Easily
accessed examples Concepts presented are technology agnostic
AUDIENCE To get the most from this book, you should have a good
foundation in Java programming and a general understanding of
internet technology. ABOUT THE TECHNOLOGY This book provides an
overview, with easy to access examples, of algorithms which learn
from data. Such algorithms have been widely adopted by many large
internet companies such as Facebook and Google and are continuing
to grow in popularity. This book has many examples in Python using
the scikit-learn library, however the concepts presented are
technology agnostic and can be easily applied with any common
programming language.
General
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