Python machine learning

Get on the fast track to creating computer games Ever want to develop your own computer game? Learn the practical concepts of object-oriented programming for game design using Python(r) in this easy

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems

A detailed examination of learning classifier systems (LCS), a form of machine learning system, which incorporates both Evolutionary Algorithms and Reinforcement Learning Algorithms.

A self-study textbook for readers with the mathematical background of a sophomore student of engineering or science. Describes various forms of representing information, and establishes that both reco

This is the first comprehensive introduction to computational learning theory. The author's uniform presentation of fundamental results and their applications offers AI researchers a theoretical persp

This monograph presents a visually striking exploration of Refik Anadol’s data-driven installation, created for the opening of the new BRUSK museum in Bruges. The book offers exclusive visuals and reflections on the intersection of art, technology, and memory in Anadol’s work.Working at the intersection of art, science, and technology, Refik Anadol is best known for his large-scale immersive installations and public artworks that use machine learning, AI, and big data to visualize complex systems. Anadol’s work transforms raw data – ranging from urban landscapes to brainwaves – into dynamic, multi-sensory experiences, pushing the boundaries of how we perceive space, memory, and reality.For the inaugural programme at BRUSK, the new museum for contemporary art in Bruges, Belgium, Anadol presents a major site-specific installation that immerses visitors in a datadriven landscape unique to the city.

Operations Research uses a balanced combination of theory, applications and computations to help you learn the basics of operating research (OR). It focuses on algorithmic and practical implementation of OR techniques. Easy-to-understand numerical examples explain often difficult math concepts, helping you grasp the foundational idea without getting stuck on complex theorems or notations. Full case studies and math-free anecdotes show how algorithms are used in real-life applications.The 11th Edition introduces analytics, artificial intelligence, and machine learning topics that strengthen and streamline the decision-making processes involved in OR. New stories, 3 new chapters, new case studies and sections provide an up-to-date introduction to the field of OR.

A concise but informative overview of AI ethics and policy.Artificial intelligence, or AI for short, has generated a staggering amount of hype in the past several years. Is it the game-changer it's been cracked up to be? If so, how is it changing the game? How is it likely to affect us as customers, tenants, aspiring homeowners, students, educators, patients, clients, prison inmates, members of ethnic and sexual minorities, and voters in liberal democracies? Authored by experts in fields ranging from computer science and law to philosophy and cognitive science, this book offers a concise overview of moral, political, legal and economic implications of AI. It covers the basics of AI's latest permutation, machine learning, and considers issues such as transparency, bias, liability, privacy, and regulation.Both business and government have integrated algorithmic decision support systems into their daily operations, and the book explores the implications for our lives as citizens. For exam

Elementary Linear Algebra: Applications Version, 12th Edition, gives an elementary treatment of linear algebra that is suitable for a first course for undergraduate students. The classic treatment of linear algebra presents the fundamentals in the clearest possible way, examining basic ideas by means of computational examples and geometrical interpretation. It proceeds from familiar concepts to the unfamiliar, from the concrete to the abstract. Readers consistently praise this outstanding text for its expository style and clarity of presentation. In this edition, a new section has been added to describe the applications of linear algebra in emerging fields such as data science, machine learning, climate science, geomatics, and biological modeling. New exercises have been added with special attention to the expanded early introduction to linear transformations and new examples have been added, where needed, to support the exercise sets. Calculus is not a prerequisite, but there are clea

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Discover a practical, streamlined approach to systems development that focuses on the latest developments with Tilley's Systems Analysis and Design, Cengage International Edition, 13th, and MindTap digital resources. Real examples clearly demonstrate both traditional and emerging approaches to systems analysis and design, including object-oriented and agile methods. You also study emerging technologies such as artificial intelligence (AI), machine learning (ML), cloud computing and cybersecurity. Meaningful projects, insightful assignments and both online and printed exercises emphasize the critical thinking and IT skills that are most important in today's dynamic, business-related environment.