I've examined every one and Cipani's is clearly the best. The assessment part is great, and I particularly like the protocol format for interventions. Cipani's text nicely fills a big gap between research and application. Were I teaching a seminar to clinicians, I think the text would be perfect. -- Brian A. Iwata, PhD, University of FloridaProfessionals who work in mental health and educational settings are frequently faced with clients (children, adolescents, adults) who engage in serious problem behaviors. Such behaviors often impact the client's welfare and ability to live, work, and be educated in mainstream environments. Children and adolescents who manifest these behaviors are particularly vulnerable to these disruptions, which can have a far-reaching impact on their development and future prospects.This practical book, written both for clinician/educators and high-level students, creates a function-based behavioral diagnostic classification system, the first of its kind, as well as treatment protocols that fit such a diagnostic system. Heavily practitioner-oriented, the book will address the full range of behaviors - ranging from aggression, self-injury, stereotypic behavior (repetitive body movements), tantrums, and non-compliance - with real life and hypothetical cases to help clinicians think through the full range of treatment options. Unique in moving beyond functional assessment to assessment diagnosis and treatment, this book will be highly useful for mental health clinicians, students of Advanced Behavior Analysis, and special education practitioners among others.Professor Cipani has also prepared extensive ancillary material for use in teaching this book and will make it available to anyone who has adopted it for course use. Instructors who have adopted the title may inquire of Professor Cipani at ennioc26@hotmail.com

    New problems added throughout.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.

    Authors Alex Banks and Eve Porcello show you how to create UIs with this small JavaScript library that can deftly display data changes on large-scale, data-driven websites without page reloads. Along the way, you'll learn how to work with functional programming and the latest ECMAScript features.Developed by Facebook, and used by companies including Netflix, Walmart, and The New York Times for large parts of their web interfaces, React is quickly growing in use. By learning how to build React components with this hands-on guide, you'll fully understand how useful React can be in your organization.Learn key functional programming concepts with JavaScriptPeek under the hood to understand how React runs in the browserCreate application presentation layers by mounting and composing React componentsUse component trees to manage data and reduce the time you spend debugging applicationsExplore React's component lifecycle and use it to load data and improve UI performanceUse a routing solution for browser history, bookmarks, and other features of single-page applicationsLearn how to structure React applications with servers in mind

     Data Structures and Algorithms in Python is the first mainstream object-oriented book available for the Python data structures course. Designed to provide a comprehensive introduction to data structures and algorithms, including their design, analysis, and implementation, the text will maintain the same general structure as Data Structures and Algorithms in Java and Data Structures and Algorithms in C++.

    Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.

    Beginning with the background and very nature of probability theory, the book then proceeds through sample spaces, combinatorial analysis, fluctuations in coin tossing and random walks, the combination of events, types of distributions, Markov chains, stochastic processes, and more. The book's comprehensive approach provides a complete view of theory along with enlightening examples along the way.

    But as the field evolves, designers enter the field from many disciplines. Practitioners today have enough experience in UI design that they have been exposed to design rules, but it is essential that they understand the psychology behind the rules in order to effectively apply them. In "Designing with the Mind in Mind," Jeff Johnson, author of the best selling "GUI Bloopers," provides designers with just enough background in perceptual and cognitive psychology that UI design guidelines make intuitive sense rather than being just a list of rules to follow. * The first practical, all-in-one source for practitioners on user interface design rules and why, when and how to apply them.* Provides just enough background into the reasoning behind interface design rules that practitioners can make informed decisions in every project.* Gives practitioners the insight they need to make educated design decisions when confronted with tradeoffs, including competing design rules, time constrictions, or limited resources.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

    Uniquely organized around concepts and use cases, this updated fifth edition features a reorganized section on concurrency, threading, and parallel programming—including in-depth coverage of C# 5.0’s new asynchronous functions.Shaped by more than 20 expert reviewers, including Microsoft’s Eric Lippert, Stephen Toub, Chris Burrows, and Jon Skeet, this book has all you need to stay on track with C# 5.0. It’s widely known as the definitive reference on the language.Get up to speed on C# language basics, including syntax, types, and variablesExplore advanced topics such as unsafe code and type varianceDig deep into LINQ via three chapters dedicated to the topicLearn about code contracts, dynamic programming, and parallel programmingWork with .NET features, including reflection, assemblies, memory management, security, I/O, XML, collections, networking, and native interoperability"C# 5.0 in a Nutshell is one of the few books I keep on my desk as a quick reference." —Scott Guthrie, Microsoft"Whether you’re a novice programmer or an expert who wants to improve your knowledge of modern asynchronous programming techniques, this book has the information you need to get the job done in C#." —Eric Lippert, Microsoft

    Distinguishing agents (e.g., molecules, cells, animals, and species) from their interactions (e.g., chemical reactions, immune system responses, sexual reproduction, and evolution), Flake argues that it is the computational properties of interactions that account for much of what we think of as beautiful and interesting. From this basic thesis, Flake explores what he considers to be today's four most interesting computational topics: fractals, chaos, complex systems, and adaptation.Each of the book's parts can be read independently, enabling even the casual reader to understand and work with the basic equations and programs. Yet the parts are bound together by the theme of the computer as a laboratory and a metaphor for understanding the universe. The inspired reader will experiment further with the ideas presented to create fractal landscapes, chaotic systems, artificial life forms, genetic algorithms, and artificial neural networks.

     Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.

    But while most of us today can work a computer--albeit with the help of the ever-present computer software manual--we know little about what goes on inside the box and virtually nothing about software designor the world of computer programming. In Patterns of Software, the respected software pioneer and computer scientist, Richard Gabriel, gives us an informative inside look at the world of software design and computer programming and the business that surrounds them. In this wide-ranging volume, Gabriel discusses such topics as whatmakes a successful programming language, how the rest of the world looks at and responds to the work of computer scientists, how he first became involved in computer programming and software development, what makes a successful software business, and why his own company, Lucid, failed in 1994, tenyears after its inception. Perhaps the most interesting and enlightening section of the book is Gabriel's detailed look at what he believes are the lessons that can be learned from architect Christopher Alexander, whose books--including the seminal A Pattern Language--have had a profound influence on the computer programmingcommunity. Gabriel illuminates some of Alexander's key insights--the quality without a name, pattern languages, habitability, piecemeal growth--and reveals how these influential architectural ideas apply equally well to the construction of a computer program. Gabriel explains the concept ofhabitability, for example, by comparing a program to a New England farmhouse and the surrounding structures which slowly grow and are modified according to the needs and desires of the people who live and work on the farm. Programs live and grow, and their inhabitants--the programmers--need to workwith that program the way the farmer works with the homestead. Although computer scientists and software entrepreneurs will get much out of this book, the essays are accessible to everyone and will intrigue anyone curious about Silicon Valley, computer programming, or the world of high technology.

    Most undergraduates have to undertake some form of literature review which may be daunting, this book explains it in an clear, easy to understand format. Explanations are given as to why undertaking a literature review is undertaken. Summery sections at the end of each chapter allow the reader to reflect on what they have just read, allowing the information to sink in. This book should be on every university's recommended reading list." Kerry Davis, Student Nurse, University Campus Suffolk, UK" ""This book is fantastic! It gives a clear, concise guide to carrying out a literature review, which is of course a widely used formative assessment technique in a nursing program ... (it includes) in depth explanations and reasons as to how and why it is important to do a literature review ... the summary section at the end of each chapter is excellent, and allows the reader to review their understanding of what they're just read. Overall an excellent book which is a must for any student nurse!" Gem Smith, Student Nurse, Northumbria University, UK"""This book is superb. It explains the entire process of writing a literature review very clearly ... extremely helpful as the prospect of reviewing literature can be quite daunting." Vicky Bain, Student Nurse, University of Nottingham, UK"A comprehensive, easy to read guide which will help students to understand how to undertake a literature review, and how to use the resultant information effectively." Anne-Marie Warnes, University of Central Lancashire, UK"As a student, currently writing a literature review, I found this an extremely helpful book, which is invaluable in demystifying some of the more challenging elements, while at the same time providing clear, simple, appealing and appropriate guidance. This is a must have for undergraduate nursing students, and indeed all healthcare students embarking on such projects." Audrey Grace, Trinity College Dublin, Dublin, Ireland"This bestselling book is a step-by-step guide to doing a literature review in health and social care. It is vital reading for all those undertaking their undergraduate or postgraduate dissertation or any research module which involves a literature review.The new edition has been fully updated and provides a practical guide to the different types of literature that you may come across when undertaking a literature review. It includes: Examples of commonly occurring real life scenarios encountered by students Emphasis on the importance of setting a question at the very start of the project Advice on how to follow a clearly defined search strategy Details of a wide range of critical appraisal tools "Doing a Literature Review in Health and Social Care 2/e" is essential reading for students at all levels within the health and social care field - and a useful text for anyone new to reviewing and appraising evidence.