Free PDF Download: A First Course in Machine Learning, Second Edition

Hina anum September 22, 2023

AI & ML Books General Books
March 21, 2023
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“A First Course in Machine Learning” is a free PDF book written by Simon Rogers, designed for beginners who want to learn the fundamentals of machine learning. The book covers a broad range of topics, including regression, classification, clustering, neural networks, deep learning, and reinforcement learning.

Machine learning has emerged as a crucial field in the world of technology, and with the increasing demand for machine learning experts, more and more people are showing interest in learning the fundamentals of this field. “A First Course in Machine Learning,” written by Simon Rogers, is an excellent resource for beginners who want to learn the basics of machine learning.

The second edition of “A First Course in Machine Learning” is a free book that provides a comprehensive overview of the subject. The book is designed to be accessible to readers with minimal prior knowledge of machine learning. It covers essential concepts such as regression, classification, clustering, and deep learning, among others.

Author: Simon Rogers
Edition: 2nd Edition
Publisher: Chapman and Hall/CRC
Published: August 15, 2016
Language: English
Pages: 307 Pages
File Size: 7.11 MB
ISBN: 978-1498738484

It is aimed at beginners who have some programming knowledge, but no prior experience with machine learning. The authors provide clear and concise explanations of the key concepts and techniques and use examples and exercises to help readers build their understanding. And also considers general books.

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Amazon

The book is well-organized and follows a logical progression, starting with an introduction to machine learning and then moving on to the various types of algorithms used in the field. Each chapter builds upon the previous one, making it easy for readers to follow along and understand the concepts.

About Author:

Simon Rogers is a well-known figure in the field of machine learning and data science. He is a professor of data science at the University of Glasgow in Scotland, where he teaches courses on machine learning, data visualization, and data analysis. He is also the Director of the Data Science and AI Division at the university.

Before joining the faculty at the University of Glasgow, Rogers was a research scientist at the Xerox Research Centre Europe, where he worked on machine learning, computer vision, and natural language processing. He has also worked as a data analyst for the Guardian, a prominent British newspaper.

In addition to his academic and industry work, Rogers is also an author and has written several books on machine learning and data science. His book "A First Course in Machine Learning" is a popular resource for beginners in the field, and it has been translated into several languages.

Rogers is also active in the machine learning community and has served as the chair of the British Machine Vision Association, the program chair for the European Conference on Computer Vision, and the general chair for the Conference on Computer Vision and Pattern Recognition. Overall, Simon Rogers is a respected expert in the field of machine learning and data science. His work as a professor, researcher, author, and community leader has helped to advance the field and inspire a new generation of machine learning practitioners.

About Book:

The book is part of the Machine Learning and Pattern Recognition series and covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning.

One of the strengths of this book is its structure, which is well-organized and follows a logical progression. The author starts with an introduction to machine learning and then moves on to the various types of algorithms used in the field. Each chapter builds upon the previous one, making it easy for readers to follow along and understand the concepts.

The book also provides practical examples and exercises that allow readers to apply the concepts they have learned. The examples are presented in Python, which is a popular programming language used in machine learning. This makes it easy for readers to experiment with the code and see how the algorithms work in practice.

Another highlight of this book is its clear and concise writing style. The author avoids using technical jargon and instead focuses on explaining concepts in a way that is easy to understand. The book is also full of helpful diagrams and illustrations that help readers visualize the concepts being discussed.

Overall, "A First Course in Machine Learning" is an excellent resource for anyone who wants to learn the basics of machine learning. The book is accessible to beginners, yet comprehensive enough to provide a solid foundation for further study. With its clear writing style, practical examples, and exercises, this book is a valuable resource for anyone interested in this exciting and rapidly growing field.