The ultimate aim of artificial intelligence (A.I.) is to understand intelligence and to build intelligent software and robots that come close to the performance of humans. On their way towards this goal, A.I. researchers have developed a number of quite different subdisciplines.

This concise and accessible Introduction to Artificial Intelligence supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The textbook presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under...

Semantics will have an important role to play in the future development of software systems and domain specific languages, and there is a real need for an introductory book that presents the fundamental ideas behind these approaches; stresses their relationship by formulating and proving the relevant theorems; and illustrates the applications of semantics in computer science.

This book investigates the relationship between the various methods and describes some of the main ideas used, illustrating these via interesting applications. Historically important application areas...

Many textbooks on computer vision can be unwieldy and intimidating in their coverage of this extensive discipline. This textbook addresses the need for a concise overview of the fundamentals of this field.

Concise Computer Vision provides an accessible general introduction to the essential topics in computer vision, highlighting the role of important algorithms and mathematical concepts. Classroom-tested programming exercises and review questions are also supplied at the end of each chapter.

This clearly structured and easy to read textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently.

Project-oriented and classroom-tested, the book presents a number of important algorithms supported by motivating examples that bring meaning to the problems faced by computer programmers. The idea of computational complexity is also introduced, demonstrating what can and cannot be computed efficiently so that the programmer can make informed judgements about the algorithms they use. The text assumes some basic experience...

This easy-to-follow and classroom-tested textbook guides the reader through the fundamentals of programming with Python, an accessible language which can be learned incrementally. This revised and updated new edition will teach students how to recognize and apply abstract patterns in programming through the extensive use of illustrative examples and practical exercises. The book also demonstrates the benefit of using a debugger to inspect the state of a program while it is executing.

Topics and features: incudes numerous examples and practice exercises throughout the text, with...

This book is about the harmonious synthesis of functional programming and numerical computation. It shows how the expressiveness of OCaml allows for fast and safe development of data science applications. Step by step, the authors build up to use cases drawn from many areas of Data Science, Machine Learning, and AI, and then delve into how to deploy at scale, using parallel, distributed, and accelerated frameworks to gain all the advantages of cloud computing environments.

To this end, the book is divided into three parts, each focusing on a different area. Part I begins by...