Machine Learning: An Applied Mathematics Introduction
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Book Overview
Machine Learning: An Applied Mathematics Introduction covers the essential mathematics behind all of the following topics
K Nearest Neighbours K Means Clustering Na ve Bayes Classifier Regression Methods Support Vector Machines Self-Organizing Maps Decision Trees Neural Networks Reinforcement LearningThe book includes many real-world examples from a variety of fields including
finance (volatility modelling) economics (interest rates, inflation and GDP) politics (classifying politicians according to their voting records, and using speeches to determine whether a politician is left or right wing) biology (recognising flower varieties, and using heights and weights of adults to determine gender) sociology (classifying locations according to crime statistics) gambling (fruit machines and Blackjack) business (classifying the members of his own website to see who will subscribe to his magazine )Paul Wilmott brings three decades of experience in mathematics education, and his inimitable style, to the hottest of subjects. This book is an accessible introduction for anyone who wants to understand the foundations but also wants to "get to the meat without having to eat too many vegetables."
Format:Paperback
Language:English
ISBN:1916081606
ISBN13:9781916081604
Release Date:May 2019
Publisher:Panda Ohana Publishing
Length:242 Pages
Weight:0.70 lbs.
Dimensions:0.5" x 6.1" x 9.2"
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