Physics of Data Science and Machine Learning

Physics of Data Science and Machine Learning
Author :
Publisher : CRC Press
Total Pages : 182
Release :
ISBN-10 : 9781000450477
ISBN-13 : 1000450473
Rating : 4/5 (473 Downloads)

Book Synopsis Physics of Data Science and Machine Learning by : Ijaz A. Rauf

Download or read book Physics of Data Science and Machine Learning written by Ijaz A. Rauf and published by CRC Press. This book was released on 2021-11-28 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Physics of Data Science and Machine Learning links fundamental concepts of physics to data science, machine learning, and artificial intelligence for physicists looking to integrate these techniques into their work. This book is written explicitly for physicists, marrying quantum and statistical mechanics with modern data mining, data science, and machine learning. It also explains how to integrate these techniques into the design of experiments, while exploring neural networks and machine learning, building on fundamental concepts of statistical and quantum mechanics. This book is a self-learning tool for physicists looking to learn how to utilize data science and machine learning in their research. It will also be of interest to computer scientists and applied mathematicians, alongside graduate students looking to understand the basic concepts and foundations of data science, machine learning, and artificial intelligence. Although specifically written for physicists, it will also help provide non-physicists with an opportunity to understand the fundamental concepts from a physics perspective to aid in the development of new and innovative machine learning and artificial intelligence tools. Key Features: Introduces the design of experiments and digital twin concepts in simple lay terms for physicists to understand, adopt, and adapt. Free from endless derivations; instead, equations are presented and it is explained strategically why it is imperative to use them and how they will help in the task at hand. Illustrations and simple explanations help readers visualize and absorb the difficult-to-understand concepts. Ijaz A. Rauf is an adjunct professor at the School of Graduate Studies, York University, Toronto, Canada. He is also an associate researcher at Ryerson University, Toronto, Canada and president of the Eminent-Tech Corporation, Bradford, ON, Canada.


Physics of Data Science and Machine Learning Related Books

Physics of Data Science and Machine Learning
Language: en
Pages: 182
Authors: Ijaz A. Rauf
Categories: Computers
Type: BOOK - Published: 2021-11-28 - Publisher: CRC Press

DOWNLOAD EBOOK

Physics of Data Science and Machine Learning links fundamental concepts of physics to data science, machine learning, and artificial intelligence for physicists
The Statistical Physics of Data Assimilation and Machine Learning
Language: en
Pages: 207
Authors: Henry D. I. Abarbanel
Categories: Computers
Type: BOOK - Published: 2022-02-17 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

The theory of data assimilation and machine learning is introduced in an accessible manner for undergraduate and graduate students.
Data-Driven Science and Engineering
Language: en
Pages: 615
Authors: Steven L. Brunton
Categories: Computers
Type: BOOK - Published: 2022-05-05 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLABĀ®.
Data Science and Machine Learning
Language: en
Pages: 538
Authors: Dirk P. Kroese
Categories: Business & Economics
Type: BOOK - Published: 2019-11-20 - Publisher: CRC Press

DOWNLOAD EBOOK

Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked
Doing Data Science
Language: en
Pages: 320
Authors: Cathy O'Neil
Categories: Computers
Type: BOOK - Published: 2013-10-09 - Publisher: "O'Reilly Media, Inc."

DOWNLOAD EBOOK

Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you