Machine Learning for Business Analytics: Concepts, Techniques, and Applications in Python is a comprehensive introduction to and an overview of the methods that underlie modern AI. This best-selling textbook covers both statistical and machine learning (AI) algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, network analytics and generative AI. Along with hands-on exercises and real-life case st...

This revision of Dummit and Foote's widely acclaimed introduction to abstract algebra helps students experience the power and beauty that develops from the rich interplay between different areas of mathematics. The book carefully develops the theory of different algebraic structures, beginning from basic definitions to some in-depth results, using numerous examples and exercises to aid the student's understanding. With this approach, students gain an appreciation for how mathematical structur...

In an age when electronic health records (EHRs) are an increasingly important source of data, this essential textbook provides both practical and theoretical guidance to researchers conducting epidemiological or clinical analysis through EHRs.

A statistical national treasure' Jeremy Vine, BBC Radio 2'Required reading for all politicians, journalists, medics and anyone who tries to influence people (or is influenced) by statistics. A tour de force' Popular ScienceDo busier hospitals have higher survival rates? How many trees are there on the planet? Why do old men have big ears? David Spiegelhalter reveals the answers to these and many other questions - questions that can only be addressed using statistical science. Statistics has p...

A textbook for students with some background in probability that develops quickly a rigorous theory of Markov chains and shows how actually to apply it, e.g. to simulation, economics, optimal control, genetics, queues and many other topics, and exercises and examples drawn both from theory and practice.

Measure and integration are key topics in many areas of mathematics, including analysis, probability, mathematical physics and finance. This book offers a concise yet elementary introduction in which the theory is quickly and simply developed. Few prerequisites are required, making the text suitable for undergraduate lecture courses or self-study.

Introductory Statistics, 10th edition, is written for a one- or two-semester first course in applied statistics and is intended for students who do not have a strong background in mathematics. The only prerequisite is knowledge of elementary algebra. Known for its realistic examples and exercises, clarity and brevity of presentation, and soundness of pedagogical approach, the book encourages statistical interpretation and literacy regardless of student background.

The book employs a clear and...

This leads to di?culties in that, although many of the elementary properties of ?nite-dimensional vector spaces hold in in?nite-dimensional vector spaces, many others do not. Since a norm on a vector space gives rise to a metric on the space, it is now possible to do analysis in the space.

This is the flash drive for The Practice of Statistics. The Practice of Statistics is the most trusted program for AP (R) Statistics because it provides teachers and students with everything they need to be successful in the statistics course and on the AP (R) Exam.

When faced with a ’human error’ problem, you may be tempted to ask 'Why didn’t these people watch out better?' Or, 'How can I get my people more engaged in safety?' You might think you can solve your safety problems by telling your people to be more careful, by reprimanding the miscreants, by issuing a new rule or procedure and demanding compliance. These are all expressions of 'The Bad Apple Theory' where you believe your system is basically safe if it were not for those few unreliable...