Learn how to train for maximum gains with Periodization: Theory and Methodology of Training. Guided by the expertise of Tudor O. Bompa, the pioneer of periodization training, and leading periodization researcher G. Gregory Haff, you’ll learn how to vary the intensity and volume of training to optimize the body’s ability to recover and rebuild—resulting in better performance and less risk of injury. Translated into nine languages, Periodization: Theory and Methodology of Training has become one of the major resources on periodization for sport scientists, coaches, and athletes throughout the world. Since the introduction of this groundbreaking training theory by Tudor O. Bompa in 1963, periodization has become the basis of every serious athlete’s training. Now in its fifth edition, Bompa’s classic text combines the concepts central to periodization and training theory with contemporary advances in sport science, physiology, and coaching. No other text discusses planning and periodization in such detail or with so many specific, practical examples from a variety of sports. With the fifth edition of Periodization, you can learn the principles, objectives, and components of a successful long-term training program and how to plan the right program to achieve your performance goals. Periodization also contains proven strategies for optimal peaking and specifics on training for better motor ability, working capacity, skill effectiveness, and psychological adaptability. Better organized and easier to read, the fifth edition of this definitive text presents the latest refinements to periodization theory: • New research on rest and restoration, specifically countermeasures used in facilitating recovery plus practical suggestions for implementation • How the use of sequential training and delayed training effects can produce optimal performance at major competitions • A comprehensive discussion, grounded in scientific data, on applying various methods of peaking to ensure optimal performance for competition • New information on how concepts such as conjugated sequencing and summated microcycle structures can maximize strength gains and direct training • Expanded information on the development of sport performance characteristics, including speed training and sport-specific endurance Chapter summaries will help you review and reference major concepts throughout the text. Plan and document each training program with ease using the duplication-ready annual and four-year training plan charts included in the appendix. When it comes to designing programs for optimal training, Tudor Bompa’s expertise is unmatched. The fifth edition of Periodization: Theory and Methodology of Training presents the latest refinements to Bompa’s periodization theory to help you create training programs that enhance sport skills and ensure peak performance.

Tudor O. Bompa, the pioneer of periodization training, and Carlo A. Buzzichelli, one of the world’s foremost experts on training methods, use scientific support and their expertise to teach you how to maximize training gains with periodization.

Sport conditioning has advanced tremendously since the era when a “no pain, no gain” philosophy guided the training regimens of athletes. Dr. Tudor Bompa pioneered most of these breakthroughs, proving long ago that it's not only how much and how hard an athlete works but also when and what work is done that determine an athlete's conditioning level. Periodization Training for Sports goes beyond the simple application of bodybuilding or powerlifting programs to build strength in athletes. In this new edition of Periodization Training for Sports, Bompa teams with strength and conditioning expert Carlo Buzzichelli to demonstrate how to use periodized workouts to peak at optimal times by manipulating strength training variables through six training phases (anatomical adaptation, hypertrophy, maximum strength, conversion to specific strength, maintenance, and tapering) and integrating them with energy system training and nutrition strategies. Coaches and athletes in 35 sports have at their fingertips a proven program that is sure to produce the best results. No more guessing about preseason conditioning, in-season workloads, or rest and recovery periods; now it's simply a matter of identifying and implementing the information in this book. Presented with plenty of ready-made training schedules, Periodization Training for Sports is your best conditioning planner if you want to know what works, why it works, and when it works in the training room and on the practice field. Get in better shape next season and reap the benefits of smarter workouts in competition. Own what will be considered the bible of strength training for sport of the next decade.

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

This book provides a comprehensive introduction to the theory and practice of diagnostic classification models (DCMs), which are useful for statistically driven diagnostic decision making. DCMs can be employed in a wide range of disciplines, including educational assessment and clinical psychology. For the first time in a single volume, the authors present the key conceptual underpinnings and methodological foundations for applying these models in practice. Specifically, they discuss a unified approach to DCMs, the mathematical structure of DCMs and their relationship to other latent variable models, and the implementation and estimation of DCMs using Mplus. The book's highly accessible language, real-world applications, numerous examples, and clearly annotated equations will encourage professionals and students to explore the utility and statistical properties of DCMs in their own projects. This book will appeal to professionals in the testing industry; professors and students in educational, school, clinical, and cognitive psychology. It will also serve as a useful text in doctoral-level courses in diagnostic testing, cognitive diagnostic assessment, test validity, diagnostic assessment, advanced educational measurement, psychometrics, and item response theory

This book answers in detail the many unanswered questions relating to high performance. Written by the world's leading gymnastics coach and his scientific advisor it explains the essential components for planning and preparation for high level results.

Simulated Patient Methodology is a timely book, aimed at health professional educators and Simulated Patient (SP) practitioners. It connects theory and evidence with practice to ensure maximum benefit for those involved in SP programmes, in order to inform practice and promote innovation. The book provides a unique, contemporary, global overview of SP practice, for all health sciences educators. Simulated Patient Methodology: • Provides a cross-disciplinary overview of the field • Considers practical issues such as recruiting and training simulated patients, and the financial planning of SP programmes • Features case studies, illustrating theory in practice, drawn from across health professions and countries, to ensure relevance to localised contexts Written by world leaders in the field, this invaluable resource summarises the theoretical and practical basis of all human-based simulation methodologies.