Computer Science Textbooks Cambridge University Press Spring 21

Higher Education

Computer Science New and bestselling textbooks

Spring 2021

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Contents MACHINE LEARNING, AI AND ROBOTICS

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Mathematics for Machine Learning Essentials of Pattern Recognition Machine Learning Refined Bayesian Reasoning and Machine Learning Understanding Machine Learning Machine Learning Natural Language Processing Artificial Intelligence Modern Robotics Computer Vision

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DATA SCIENCE

Computer Age Statistical Inference, Student Edition A Hands-On Introduction to Data Science Mining of Massive Datasets Data Mining and Machine Learning Foundations of Data Science A First Course in Statistical Programming with R Modern Statistics for Modern Biology Data-Driven Science and Engineering Principles of Database Management Introduction to Information Retrieval

QUANTUM COMPUTING

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Quantum Computation and Quantum Information 10 Quantum Computing since Democritus 10 Quantum Computing for Computer Scientists 11 Quantum Computer Science 11

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6 6 6 6 6 6 7 7 7 7

FOUNDATIONS 7

Probability and Computing 7 How to Prove It 7 Combinatorial Mathematics 7 Introduction to Applied Linear Algebra 7 Linear Algebra and Learning from Data 9 The Probability Companion for Engineering and Computer Science 9 Logic in Computer Science 9 Computational Complexity 9 Digital Design Using VHDL 9 NETWORK SCIENCE

A First Course in Network Science Network Science Networks, Crowds and Markets

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9 9 9

PROGRAMMING AND SOFTWARE DEVELOPMENT 10

Competitive Programming in Python Programming in Haskell Introduction to Software Testing Modern Compiler Implementation in Java Modern Compiler Implementation in ML Modern Compiler Implementation in C

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Higher Education | Computer Science

MACHINE LEARNING, AI AND ROBOTICS

Mathematics for Machine Learning Marc Peter Deisenroth A. Aldo Faisal Cheng Soon Ong

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

Understanding Machine Learning From Theory to Algorithms Shai Shalev-Shwartz Shai Ben-David

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

July 2014 253 x 177 mm 410pp 47 b/w illus. 123 exercises 978-1-107-05713-5 Hardback £45.99 / US$59.99 P

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.

November 2020 244 x 170 mm 398pp 978-1-108-48346-9 Hardback £49.99 / US$69.99 X

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 £40.99 / US$53.99 P

Machine Learning Refined Foundations, Algorithms, and Applications Second edition Jeremy Watt Reza Borhani 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 David Barber

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

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

Natural Language Processing

Artificial Intelligence

A Machine Learning Perspective Yue Zhang Zhiyang Teng

Foundations of Computational Agents Second edition David L. Poole Alan K. Mackworth

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

January 2021 246 x 189 mm 484pp 978-1-108-42021-1 Hardback £53.99 / US$69.99 P

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

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

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Higher Education | Computer Science

Modern Robotics

Computer Vision

Mechanics, Planning, and Control Kevin M. Lynch Frank C. Park

Models, Learning, and Inference Simon J. D. Prince

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 544pp 978-1-107-15630-2 Hardback £60.99 / US$77.99 X

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

DATA SCIENCE

Computer Age Statistical Inference, Student Edition Algorithms, Evidence, and Data Science Bradley Efron, Trevor Hastie

Now in paperback and fortified with exercises, this brilliant, enjoyable text demystifies data science, statistics and machine learning.

A Hands-On Introduction to Data Science Chirag Shah

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

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

Institute of Mathematical Statistics Monographs, 6 June 2021 228 x 152 mm c.510pp 978-1-108-82341-8 Paperback c. £29.99 / c. US$39.99 P TH IR D EDITION

A FIR ST COU R SE

I N STATISTIC A L

PROGR A M M I NG W ITH

R

W. John Braun Duncan J. Murdoch

Mining of Massive Datasets

Data Mining and Machine Learning

Foundations of Data Science

Third edition Jure Leskovec Anand Rajaraman Jeffrey David Ullman

Fundamental Concepts and Algorithms Second edition Mohammed J. Zaki Wagner Meira, Jr

Avrim Blum John Hopcroft Ravindran Kannan

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

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

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

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

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 P

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A First Course in Statistical Programming with R Third edition W. John Braun Duncan J. Murdoch

Get started computing with data.

Learn general principles while learning R – now including the tidyverse.

May 2021 246 x 189 mm c.275pp 978-1-108-99514-6 Paperback £34.99 / US$44.99 P

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Higher Education | Computer Science

Modern Statistics for Modern Biology Susan Holmes 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

Data-Driven Science and Engineering Machine Learning, Dynamical Systems, and Control Steven L. Brunton J. Nathan Kutz

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

FOUNDATIONS

Probability and Computing Randomization and Probabilistic Techniques in Algorithms and Data Analysis Second edition Michael Mitzenmacher Eli Upfal

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

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

Principles of Database Management The Practical Guide to Storing, Managing and Analyzing Big and Small Data Wilfried Lemahieu Seppe vanden Broucke, Bart Baesens

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

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

Introduction to Information Retrieval Christopher D. Manning Prabhakar Raghavan 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

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

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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Data Science and Data Mining

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Higher Education | Computer Science

Linear Algebra and Learning from Data Gilbert Strang

From Gilbert Strang, the first textbook that teaches linear algebra together with deep learning and neural nets.

NOT FOR SALE IN NORTH AMERICA January 2019 234 x 191 mm 446pp 978-0-692-19638-0 Hardback £58.99 / US$74.99 X

The Probability Companion for Engineering and Computer Science Adam Prügel-Bennett

Using examples and building intuition, this friendly guide helps readers understand and use probabilistic tools from basic to sophisticated.

January 2020 253 x 177 mm 470pp 356 b/w illus.

978-1-108-72770-9 Paperback £39.99 / US$52.99 P

From the origins of the six degrees of separation to explaining why networks are robust to failures fragile to attacks, the author explores how viruses such as Ebola and H1N1 spread, and why it is that our friends have more friends than we do. Using numerous real-world examples, this innovatively designed text includes clear delineation between undergraduate- and graduate-level material. The mathematical formulas and derivations are included within Advanced Topics sections, enabling use at a range of levels. Extensive online resources (barabasi.com/networksciencebook), including films and software for network analysis, make this a multi-faceted companion for anyone with an interest in network science.

Albert-László Barabási is Robert Gray Dodge Professor of Network Science and Director of the Center for Complex Network Research at Northeastern University, with appointments at the Harvard Medical School and the Central European University in Budapest. His work in network science has led to the discovery of scale-free networks and elucidated many key network properties, from robustness to control.

9781107076266: Barabasi: PPC: C M Y K

Digital Design Using VHDL A Systems Approach William J. Dally R. Curtis Harting Tor M. Aamodt

Cover illustration: The nodes on the cover represent concepts discussed in the book, connected if they are covered in the same section. The resulting network captures the discipline’s ability to wave together different ideas into a coherent framework. Text analysis and visualization by Mauro Martino and Steven Ross.

Cover design: Andrew Ward

NETWORK SCIENCE

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

Provides students with a systemlevel perspective and the tools they need to analyze and design complete digital systems using VHDL.

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

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

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

Barabási NETWORK SCIENCE

Networks are everywhere, from the internet, to social networks, and the genetic networks that determine our biological existence. Illustrated throughout in full color, this pioneering textbook, spanning a wide range of topics from physics to computer science, engineering, economics and social sciences, introduces network science to an interdisciplinary audience.

Logic in Computer Science

Computational Complexity

Modelling and Reasoning about Systems Second edition Michael Huth Mark Ryan

A Modern Approach Sanjeev Arora Boaz Barak

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

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

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

June 2009 253 x 215 mm 594pp 73 b/w illus. 6 tables 307 exercises 978-0-521-42426-4 Hardback £49.99 / US$64.99 P

Albert-László Barabási

NETWORK SCIENCE Network Science Second edition 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

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Networks, Crowds, and Markets Reasoning about a Highly Connected World David Easley Jon Kleinberg

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

September 2010 253 x 215 mm 744pp 332 b/w illus. 128 exercises 978-0-521-19533-1 Hardback £49.99 / US$64.99 P

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Higher Education | Computer Science

PROGRAMMING AND SOFTWARE DEVELOPMENT

Competitive Programming in Python 128 Algorithms to Develop your Coding Skills Christoph Dürr, Jill-Jênn Vie Greg Gibbons, Danièle Gibbons

All the algorithms, proofs, and implementations in Python you need to know for tech job interviews and coding competitions.

Programming in Haskell

Introduction to Software Testing

Second edition Graham Hutton

Second edition Paul Ammann Jeff Offutt

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

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

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

Modern Compiler Implementation in Java Second edition Andrew W. Appel Jens Palsberg

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

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

December 2020 244 x 170 mm 264pp 978-1-108-71682-6 Paperback £29.99 / US$39.99 P

Modern Compiler Implementation in ML

Modern Compiler Implementation in C

Andrew W. Appel

Andrew W. Appel Maia Ginsburg

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

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 556pp 80 b/w illus. 34 tables 117 exercises 978-0-521-60765-0 Paperback £59.99 / US$87.99

QUANTUM COMPUTING

Quantum Computation and Quantum Information 10th Anniversary Edition Michael A. Nielsen Isaac L. Chuang

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

Quantum Computing since Democritus Scott Aaronson

Takes students and researchers on a tour through some of the deepest ideas of maths, computer science and physics.

March 2013 228 x 152 mm 398pp 25 b/w illus.

978-0-521-19956-8 Paperback £37.99 / US$49.99 P

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

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Higher Education | Computer Science

Quantum Computing for Computer Scientists Noson S. Yanofsky Mirco A. Mannucci

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

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

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