Computer Science Textbooks from Cambridge University Press Fall 2020

Higher Education

Computer Science New and bestselling textbooks

Fall 2020

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Higher Education | Computer Science

Mathematics for Machine Learning

Machine Learning Refined

Marc Peter Deisenroth A. Aldo Faisal and Cheng Soon Ong

Foundations, Algorithms, and Applications

Distills key concepts from linear algebra, geometry, matrices, calculus, optimization, probability and statistics that are used in machine learning.

April 2020 253 x 177 mm c.398pp 3 b/w illus. 106 colour illus.

978-1-108-45514-5 Paperback £35.99 / US$46.99 P

Second edition Jeremy Watt, Reza Borhani and Aggelos K. Katsaggelos

An intuitive approach to machine learning covering key concepts, real-world applications, and practical Python coding exercises.

January 2020 247 x 174 mm 594pp 316 colour illus. 127 exercises 978-1-108-48072-7 Hardback £52.99 / US$69.99 X

Bayesian Reasoning and Machine Learning

A Hands-On Introduction to Data Science

David Barber

Chirag Shah

A practical introduction perfect for final-year undergraduate and graduate students without a solid background in linear algebra and calculus.

An introductory textbook offering a low barrier entry to data science; the hands-on approach will appeal to students from a range of disciplines.

February 2012 246 x 189 mm 735pp 287 b/w illus. 1 table 260 exercises 978-0-521-51814-7 Hardback £60.99 / US$81.99 X

April 2020 246 x 189 mm c.424pp 5 b/w illus. 135 colour illus. 36 tables 154 exercises 978-1-108-47244-9 Hardback £39.99 / US$49.99 P

Mining of Massive Datasets

Data Mining and Machine Learning

Principles of Database Management

Third edition Jure Leskovec Anand Rajaraman and Jeffrey David Ullman

Fundamental Concepts and Algorithms

The Practical Guide to Storing, Managing and Analyzing Big and Small Data

Second edition Mohammed J. Zaki and Wagner Meira, Jr

Wilfried Lemahieu Seppe vanden Broucke and Bart Baesens

New to the second edition of this advanced text are several chapters on regression, including neural networks and deep learning.

Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.

January 2020 253 x 177 mm 776pp 297 b/w illus.

978-1-108-47398-9 Hardback £57.99 / US$74.99 P

July 2018 246 x 189 mm 808pp 439 colour illus. 163 tables 978-1-107-18612-5 Hardback £54.99 / US$70.99 X

Now in its third edition, this book focuses on practical algorithms for mining data from even the largest datasets.

January 2020 244 x 170 mm c.565pp 76 b/w illus. 250 exercises 978-1-108-47634-8 Hardback £59.99 / US$74.99 P

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Essentials of Pattern Recognition An Accessible Approach

Jianxin Wu

An accessible undergraduate introduction to the concepts and methods in pattern recognition, machine learning and deep learning.

December 2020 244 x 170 mm c.395pp 978-1-108-48346-9 Hardback £49.99 / US$69.99 X

Higher Education | Computer Science

Natural Language Processing A Machine Learning Perspective

Yue Zhang and Zhiyang Teng

This undergraduate textbook introduces essential machine learning concepts in NLP in a unified and gentle mathematical framework.

Introduction to Information Retrieval Christopher D. Manning Prabhakar Raghavan and Hinrich Schütze

A class-tested and up-to-date textbook for introductory courses on information retrieval.

September 2008 253 x 177 mm 506pp 5 b/w illus. 47 tables 263 exercises 978-0-521-86571-5 Hardback £50.99 / US$70.99 X

February 2021 246 x 189 mm c.450pp 978-1-108-42021-1 Hardback c. £53.99 / c. US$69.99 P

Computer Vision Models, Learning, and Inference

Simon J. D. Prince

A modern treatment focusing on learning and inference, with minimal prerequisites, real-world examples and implementable algorithms.

August 2012 253 x 177 mm 598pp 357 colour illus. 5 tables 201 exercises 978-1-107-01179-3 Hardback £66.99 / US$89.99 X

A First Course in Network Science Filippo Menczer Santo Fortunato and Clayton A. Davis

A practical introduction to network science for students across business, cognitive science, neuroscience, sociology, biology, engineering and other disciplines.

Artificial Intelligence

Modern Robotics

Second edition David L. Poole and Alan K. Mackworth

and Frank C. Park

Mechanics, Planning, and Control

Foundations of Computational Agents Kevin M. Lynch

Artificial Intelligence presents a practical guide to AI, including agents, machine learning and problem-solving simple and complex domains.

A modern and unified treatment of the mechanics, planning, and control of robots, suitable for a first course in robotics.

May 2017 253 x 177 mm 547pp 978-1-316-60984-2 Paperback TBA / TBA -

November 2017 253 x 177 mm 820pp 978-1-107-19539-4 Hardback £58.99 / US$75.99 X

Network Science Albert-László Barabási With Márton Pósfai

Illustrated throughout in full colour, this pioneering text is the only book you need for an introduction to network science.

July 2016 246 x 189 mm 475pp 371 colour illus. 12 tables 30 exercises 978-1-107-07626-6 Hardback £41.99 / US$54.99 X

February 2020 246 x 189 mm c.300pp 131 b/w illus. 131 colour illus.

978-1-108-47113-8 Hardback £34.99 / US$44.99 X

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Modern Statistics for Modern Biology Susan Holmes and Wolfgang Huber

A far-reaching course in practical advanced statistics for biologists using R/Bioconductor, data exploration, and simulation.

February 2019 276 x 216 mm 402pp 978-1-108-70529-5 Paperback £49.99 / US$64.99 X

Higher Education | Computer Science

Quantum Computation and Quantum Information

Quantum Computing for Computer Scientists

10th Anniversary Edition

Noson S. Yanofsky and Mirco A. Mannucci

Michael A. Nielsen and Isaac L. Chuang

This 10th anniversary edition includes an introduction from the authors setting the work in context.

December 2010 247 x 174 mm 702pp 200 b/w illus. 10 tables 598 exercises 978-1-107-00217-3 Hardback £56.99 / US$75.99 X

Combinatorial Mathematics Douglas B. West

This is the most readable and thorough graduate textbook and reference for combinatorics, covering enumeration, graphs, sets, and methods.

July 2020 246 x 189 mm 988pp 2200 exercises 978-1-107-05858-3 Hardback £59.99 / US$77.99 X

Finally, a textbook that explains quantum computing using techniques and concepts familiar to computer scientists.

November 2008 253 x 177 mm 402pp 4 b/w illus. 245 exercises 978-0-521-87996-5 Hardback £65.99 / US$89.99 X

Introduction to Applied Linear Algebra Vectors, Matrices, and Least Squares

Stephen Boyd and Lieven Vandenberghe

A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.

June 2018 246 x 189 mm 474pp 978-1-316-51896-0 Hardback £35.99 / US$50.99 X

Quantum Computer Science An Introduction

N. David Mermin

A concise introduction to quantum computation for computer scientists who know nothing about quantum theory.

August 2007 246 x 189 mm 233pp 67 b/w illus.

978-0-521-87658-2 Hardback £51.99 / US$70.99 X

How to Prove It A Structured Approach

Third edition Daniel J. Velleman

Helps students transition from problem solving to proving theorems, with a new chapter on number theory and over 150 new exercises.

July 2019 228 x 152 mm 468pp 47 b/w illus.

978-1-108-43953-4 Paperback £29.99 / US$37.99 X

Probability and Computing

Logic in Computer Science

Randomization and Probabilistic Techniques in Algorithms and Data Analysis

Modelling and Reasoning about Systems

Second edition Michael Mitzenmacher and Eli Upfal

This greatly expanded new edition offers a comprehensive introduction to randomization and probabilistic techniques in modern computer science.

July 2017 253 x 177 mm 484pp 8 b/w illus. 1 table 978-1-107-15488-9 Hardback £47.99 / US$69.99 X

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Second edition Michael Huth and Mark Ryan

Provides a sound basis in logic, and introduces logical frameworks used in modelling, specifying and verifying computer systems.

August 2004 247 x 174 mm 440pp 10 tables 400 exercises 978-0-521-54310-1 Paperback £50.99 / US$65.99 X

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This textbook describes all phases of a compiler: lexical analysis, parsing, abstract syntax, semantic actions, intermediate representations, instruction selection via tree matching, dataflow analysis, graph-coloring register allocation, and runtime systems. It includes good coverage of current techniques in code generation and register

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second edition

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Programming in Haskell Second edition Graham Hutton

This extensively updated and expanded version of the bestselling first edition now covers recent and more advanced features of Haskell.

Modern Compiler Implementation in Java

Modern Compiler Implementation in ML

Second edition Andrew W. Appel With Jens Palsberg

Andrew W. Appel

The second edition features a redesigned compiler project in Java, for a subset of Java itself.

September 2016 216 x 138 mm 318pp 1 b/w illus. 120 exercises 978-1-316-62622-1 Paperback £30.99 / US$42.99 X

October 2002 246 x 156 mm 512pp 80 b/w illus. 35 tables 135 exercises 978-0-521-82060-8 Hardback £60.99 / US$94.99 X

Introduction to Software Testing

Digital Design Using VHDL

Second edition Paul Ammann and Jeff Offutt

A Systems Approach

This classroom-tested new edition features expanded coverage of the basics and test automation frameworks, with new exercises and examples.

December 2016 253 x 177 mm 364pp 79 b/w illus.

978-1-107-17201-2 Hardback £50.99 / US$70.99 X

Describes all phases of a modern compiler, including techniques in code generation and register allocation for imperative, functional and object-oriented languages.

July 2004 246 x 189 mm 552pp 80 b/w illus. 34 tables 117 exercises 978-0-521-60764-3 Paperback £56.99 / US$84.99 X

William J. Dally R. Curtis Harting and Tor M. Aamodt

Provides students with a systemlevel perspective and the tools they need to analyze and design complete digital systems using VHDL. December 2015 246 x 189 mm 721pp 489 b/w illus. 68 tables 978-1-107-09886-2 Hardback £55.99 / US$77.99 X

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Modern Compiler Implementation in C Andrew W. Appel With Maia Ginsburg

Describes all phases of a modern compiler, including techniques in code generation and register allocation for imperative, functional and objectoriented languages.

July 2004 246 x 189 mm 556pp 80 b/w illus. 34 tables 117 exercises 978-0-521-60765-0 Paperback £59.99 / US$87.99 X

Higher Education | Computer Science ALSO OF INTEREST

Foundations of Data Science Avrim Blum John Hopcroft and Ravindran Kannan

Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks.

January 2020 253 x 177 mm 432pp 978-1-108-48506-7 Hardback £38.99 / US$49.99

Networks, Crowds, and Markets Reasoning about a Highly Connected World

David Easley and Jon Kleinberg

Data-Driven Science and Engineering

Understanding Machine Learning From Theory to Algorithms

Machine Learning, Dynamical Systems, and Control

Shai Shalev-Shwartz and Shai Ben-David

Steven L. Brunton and J. Nathan Kutz

Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.

This beginning graduate textbook teaches data science and machine learning methods for modeling, prediction, and control of complex systems.

February 2019 253 x 177 mm 492pp 978-1-108-42209-3 Hardback £49.99 / US$64.99 P

July 2014 253 x 177 mm 410pp 47 b/w illus. 123 exercises 978-1-107-05713-5 Hardback £44.99 / US$64.99 P

Computational Complexity A Modern Approach

Sanjeev Arora and Boaz Barak

Reveals the interdisciplinary field of networks, which changes how we look at social, financial and technological interactions in modern society.

New and classical results in computational complexity, including interactive proofs, PCP, derandomization, and quantum computation. Ideal for graduate students.

September 2010 253 x 215 mm 744pp 332 b/w illus. 128 exercises 978-0-521-19533-1 Hardback £48.99 / US$64.99 P

June 2009 253 x 215 mm 594pp 73 b/w illus. 6 tables 307 exercises 978-0-521-42426-4 Hardback £48.99 / US$64.99 P

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Machine Learning The Art and Science of Algorithms that Make Sense of Data

Peter Flach

Covering all the main approaches in state-of-the-art machine learning research, this will set a new standard as an introductory textbook.

September 2012 246 x 189 mm 409pp 120 colour illus. 15 tables 978-1-107-42222-3 Paperback £39.99 / US$59.99 P

Notes | Computer Science

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Notes | Computer Science

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