Data science for mathematicians
Material type:
- 9780367027056
- 515 D2
Item type | Current library | Item location | Collection | Shelving location | Call number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|---|---|---|
Books | Vikram Sarabhai Library | Rack 28-A / Slot 1371 (0 Floor, East Wing) | Non-fiction | General Stacks | 515 D2 (Browse shelf(Opens below)) | Available | 204167 |
Table of Contents
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
Bibliography
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.
https://www.routledge.com/Data-Science-for-Mathematicians/Carter/p/book/9780367027056
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