This authoritative, expanded and updated third edition of Encyclopedia of Machine Learning and Data Mining provides easy access to core information for those seeking entry into any aspect within the broad field of Machine Learning and Data Mining.
A comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation.
Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models.
The premise of this handbook is to empower users and tool developers with the appropriate collection of formulas and techniques for data analytics and to serve as a quick reference to keep pertinent formulas within fingertip reach of readers.
Some useful Subject Headings for print books in our collection are: