Data Science for Mathematicians 
/ by Nathan Carter 
 - New york :  CRC Press/Taylor & Francis,  2021. 
 - xv,528p.  : ill.  ; 24 cm. 
 - CRC Press/ Chapman and Hall Handbooks in Mathematics Series .
<br/><br/> Includes bibliography and index. 
<br/><br/> Data Science for Mathematicians presents the experience and insight of mathematicians who have retrained themselves as data scientists. Readers with a mathematical background and some computing expe-rience can use this book as a pathway to teaching in a data science program or starting research in the field.Students of data science, as they learn techniques and best practices, often ask why the techniques work and how they became best practices. A. mathematical mindset is uniquely qualified to answer those why questions, and thus mathematicians' involvement makes the teaching of data science more robust.The next generation of data scientists will be trained by faculty in the related disciplines of statistics, computer science, and mathematics. While pure mathematicians may be unfamiliar with data science, they have powerful skills that, if deepened in the ways set out in this book, would prepare them not only to teach the next generation of data scientists, but also to answer compelling questions with data. Gaining such power has reinvigorated the careers of many mathematicians  
<br/><br/><label>ISBN: </label>978103294561 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Linear algebra.<br/>Clustering.<br/>Machine Learning.<br/>Dimensionality Reduction.