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| | Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Instagram, GitHub, and More
Mine the rich data tucked away in popular social websites such as Twitter, Facebook, LinkedIn, and Instagram. With the third edition of this popular guide, data scientists, analysts, and programmers will learn how to glean insights from social media—including who’s connecting with whom, what they’re... | | |
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Survey of Text Mining II: Clustering, Classification, and RetrievalThe proliferation of digital computing devices and their use in communication has resulted in an increased demand for systems and algorithms capable of mining textual data. Thus, the development of techniques for mining unstructured, semi-structured, and fully-structured textual data has become increasingly important in both academia and industry.... | | Great Jobs for Engineering Majors (Great Jobs Series)Engineer a bright future for yourself!
You've worked hard for that engineering degree. Now what? Sometimes the choice of careers can seem endless; the most difficult part of a job search is narrowing down your options.
Great Jobs for Engineering Majors will help you choose the right career out of the myriad... | | Learning Classifier Systems: From Foundations to Applications
Learning classi er systems are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a partially unknown environment through genetic algorithms and temporal di erence learning.
From the beginning, classi er systems have attracted... |
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