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A Concise Introduction to Machine Learning A.C. Faul (University of Cambridge, UK)

A Concise Introduction to Machine Learning By A.C. Faul (University of Cambridge, UK)

A Concise Introduction to Machine Learning by A.C. Faul (University of Cambridge, UK)


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A Concise Introduction to Machine Learning Summary

A Concise Introduction to Machine Learning by A.C. Faul (University of Cambridge, UK)

The emphasis of the book is on the question of Why - only if why an algorithm is successful is understood, can it be properly applied, and the results trusted. Algorithms are often taught side by side without showing the similarities and differences between them. This book addresses the commonalities, and aims to give a thorough and in-depth treatment and develop intuition, while remaining concise.

This useful reference should be an essential on the bookshelves of anyone employing machine learning techniques.

The author's webpage for the book can be accessed here.

About A.C. Faul (University of Cambridge, UK)

A.C. Faul was a Teaching Associate, Fellow and Director of Studies in Mathematics at Selwyn College, University of Cambridge. She came to Cambridge after studying two years in Germany. She did Part II and Part III Mathematics at Churchill College, Cambridge. Since these are only two years, and three years are necessary for a first degree, she does not hold one. However, this was followed by a PhD on the Faul-Powell Algorithm for Radial Basis Function Interpolation under the supervision of Professor Mike Powell. She then worked on the Relevance Vector Machine with Mike Tipping at Microsoft Research Cambridge. Ten years in industry followed where she worked on various algorithms on mobile phone networks, image processing and data visualization. Current projects are on machine learning techniques. In teaching, she enjoys to bring out the underlying, connecting principles of algorithms, which is the emphasis of a book on Numerical Analysis she has written.

Table of Contents

Chapter 1. Introduction

Chapter 2. Probability Theory

Chapter 3. Sampling

Chapter 4. Linear Classification

Chapter 5. Non-Linear Classification

Chapter 6. Dimensionality Reduction

Chapter 7. Regression

Chapter 8. Feature Learning

Additional information

CIN0815384106G
9780815384106
0815384106
A Concise Introduction to Machine Learning by A.C. Faul (University of Cambridge, UK)
Used - Good
Paperback
Taylor & Francis Inc
20190807
314
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Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a used book - there is no escaping the fact it has been read by someone else and it will show signs of wear and previous use. Overall we expect it to be in good condition, but if you are not entirely satisfied please get in touch with us

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