1st Edition

Data Science for Mathematicians

Edited By Nathan Carter Copyright 2021
    544 Pages 151 B/W Illustrations
    by Chapman & Hall

    544 Pages 151 B/W Illustrations
    by Chapman & Hall

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    Mathematicians have skills that, if deepened in the right ways, would enable them to use data to answer questions important to them and others, and report those answers in compelling ways. Data science combines parts of mathematics, statistics, computer science. Gaining such power and the ability to teach has reinvigorated the careers of mathematicians. This handbook will assist mathematicians to better understand the opportunities presented by data science. As it applies to the curriculum, research, and career opportunities, data science is a fast-growing field. Contributors from both academics and industry present their views on these opportunities and how to advantage them.


    Chapter 1 Introduction 1
    Chapter 2 Programming with Data
    Chapter 3 Linear Algebra
    Chapter 4 Basic Statistics
    Chapter 5 Clustering
    Chapter 6 Operations Research
    Chapter 7 Dimensionality Reduction
    Chapter 8 Machine Learning
    Chapter 9 Deep Learning
    Chapter 10 Topological Data Analysis


    Nathan Carter is a professor at Bentley University.