Physics of Data Science and Machine Learning

Rauf, Ijaz A.

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商品描述

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, whilst 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 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 explained strategically and explain 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 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.

商品描述(中文翻譯)

《資料科學與機器學習的物理學》將物理學的基本概念與資料科學、機器學習和人工智慧相結合,針對希望將這些技術應用於自己工作的物理學家進行了詳細的介紹。

這本書專門為物理學家撰寫,將量子力學和統計力學與現代數據挖掘、資料科學和機器學習相結合。它還解釋了如何將這些技術融入實驗設計中,同時探索了建立在統計力學和量子力學基礎上的神經網絡和機器學習。

這本書是物理學家學習如何在研究中應用資料科學和機器學習的自學工具。它也對計算機科學家和應用數學家感興趣,以及研究生學生希望了解資料科學、機器學習和人工智慧的基本概念和基礎。

儘管專門為物理學家撰寫,但它也有助於非物理學家從物理學的角度理解基本概念,以促進新的創新機器學習和人工智慧工具的發展。

主要特點:

- 以物理學家易於理解、採用和適應的簡單術語介紹實驗設計和數字孿生概念。
- 摒棄冗長的推導,而是以策略性地呈現和解釋方程式,並解釋為什麼使用它們是必要的,以及它們如何幫助完成任務。
- 插圖和簡單的解釋幫助讀者形象化和吸收難以理解的概念。

Ijaz A. Rauf是加拿大多倫多約克大學研究生院的兼職教授,也是加拿大多倫多萊爾森大學的副研究員,以及加拿大布拉德福市Eminent-Tech Corporation的總裁。

作者簡介

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.

作者簡介(中文翻譯)

Ijaz A. Rauf 是加拿大多倫多約克大學研究生院的兼職教授。他也是加拿大多倫多萊爾森大學的副研究員,以及加拿大布拉德福市 Eminent-Tech 公司的總裁。