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No Bullshit Math for Data Science: Your Comprehensive, Short and Sharp Guide to the Mathematics of Data Science

Algebra

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Description

Data science is an interdisciplinary, growing field that uses scientific methods, processes, and algorithms to extract or extrapolate knowledge, patterns, and insights from various kinds of structured, semi-structured, and unstructured data for various real-life and theoretical purposes. To become a successful data scientist, one must have a solid foundation in mathematics, programming skills, and domain expertise. A data scientist should be able to work with large datasets, manipulate and analyze data using statistical techniques, and communicate the findings effectively to stakeholders. Furthermore, a data scientist should be able to design and develop predictive models using machine learning algorithms to solve real-world problems. As someone who has been engaging with math, in one form or another, for over a decade, I find it disappointing that there aren't many books that teach the mathematics underneath data science in a comprehensive, short and sharp manner. This book aims at doing exactly that. Really, the need for writing this book is best captured by its title! There is a myriad of books on data science, machine learning and their underlying mathematics, but they're each around 350 pages long, with a high price, which only touch upon a few topics, mainly written in code, with much less actual teaching of mathematics, or doing some but in very advanced levels. The book has two parts. Part I explores the core mathematics at use in data science. Part II builds upon the knowledge gained in the first part and explores the underlying mathematics of some of the well-known machine learning algorithms and models; it also provides sample codes to implement each of the algorithms in the programming language Python.

Product Specifications

Format: paperback
ASIN: B0C47K45WH
Category: Books > Subjects > Science, Nature & Maths > Mathematics > Algebra
Domain: Amazon UK
Release Date: 07 May 2023
Listed Since: 08 May 2023

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No Bullshit Math for Data Science: Your Comprehensive, Short and Sharp Guide to the Mathematics of Data Science

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