Physics of Data Science and Machine Learning - Ijaz A. Rauf

Physics of Data Science and Machine Learning

(Autor)

Buch | Softcover
194 Seiten
2021
CRC Press (Verlag)
978-1-032-07401-6 (ISBN)
73,55 inkl. MwSt
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.
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.

Ijaz A. Rauf is 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.

Chapter 1: Introduction

Chapter 2: An Overview of Classical Mechanics

Chapter 3: An Overview of Quantum Mechanics

Chapter 4: Probabilistic Physics

Chapter 5: Design of Experiments and Analyses

Chapter 6: Basics of Machine Learning

Chapter 7: Prediction, Optimization, and New Knowledge Development

Erscheinungsdatum
Zusatzinfo 9 Tables, black and white; 48 Line drawings, black and white; 48 Illustrations, black and white
Verlagsort London
Sprache englisch
Maße 156 x 234 mm
Gewicht 453 g
Themenwelt Mathematik / Informatik Informatik Datenbanken
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Naturwissenschaften Physik / Astronomie
Technik Elektrotechnik / Energietechnik
Technik Umwelttechnik / Biotechnologie
ISBN-10 1-032-07401-9 / 1032074019
ISBN-13 978-1-032-07401-6 / 9781032074016
Zustand Neuware
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