Machine Learning

Description

A concise and comprehensive introduction to Machine Learning

Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition–as well as some we don’t yet use everyday, including driverless cars. It is the basis of the new approach in computing where we do not write programs but collect data; the idea is to learn the algorithms for the tasks automatically from data. As computing devices grow more ubiquitous, a larger part of our lives and work is recorded digitally, and as “Big Data” has gotten bigger, the theory of machine learning–the foundation of efforts to process that data into knowledge–has also advanced.

Key Features

• Hands-on implementation of machine learning in R and Python
• In-depth treatment of supervised and unsupervised learning
• Examples that showcase the use of machine learning in the industry
• 400+ sample questions and 3 full-length sample exam papers
• Written for Undergraduate Students of Computer Science