This new, third edition of Jack Phillips's classic Handbook of Training Evaluation and Measurement Methods shows the reader not only how to design, implement, and assess the effectiveness of HRD programs, but how to ultimately measure their return on investment (ROI). Each chapter has been revised and updated to include additional research, expanded coverage, and new examples of Dr. Phillips's case studies. Seven entirely new chapters have also been added, focusing largely on ROI.

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.

Since 1990, Mel Silberman’s classic book, Active Training, has been a runaway best-seller for trainers at all levels and a popular text for university level courses in adult education and training. The active training method—which turns the spotlight away from the instructor and put the emphasis on the learner—has emerged over time as a proven and reliable method for enhancing involvement, learning, and change. The third edition of Active Training, provides a thorough introduction to the core principles of active training design and delivery and includes a wealth of examples, tips, and techniques. The book has been revised to reflect the latest trends in workforce training and key sections, such as assessment and evaluation, have been thoroughly updated. In addition, a completely new chapter has been included to cover the design of active training for e-learning and online applications.

The all-time bestselling training handbook, updated for new technologies and roles Active Training turns instructional design on its head by shifting the emphasis away from the instructor, and on to the learner. Comprehensively updated to reflect the many developments in the field, this new fourth edition covers the latest technologies and applications, the evolving role of the trainer, and how new business realities impact training, advancing new evidence-based best practices for new trainer tasks, skills, and knowledge. Up to date theory and research inform the practical tips and techniques that fully engage learners and help them get the most out of sessions, while updated workplace examples and revised templates and worksheets help bring these techniques into the classroom quickly. You'll gain insight into improving training evaluation by using Return on Expectations (ROE), learn how to extend the value of training programs through transfer of learning, and develop fresh, engaging methods that incorporate state-of-the-art applications. Active Training designs offer just the right amount of content; the right balance of affective, behavioral, and cognitive learning; a variety of approaches; real-life problem solving; gradual skill-building; and engaging delivery that uses the participants' expertise as a foundation for learning. This book is the classic guide to employing Active Training methods effectively and appropriately for almost any topic. Learn how the trainer's role has changed Engage learners through any training delivery method Inspire collaboration and innovation through application Overcome the challenges trainers face in the new business environment Active Training methods make training sessions fun, engaging, relevant, and most importantly, effective. Participants become enthusiastic about the material, and view sessions as interesting challenges rather than as means to fulfill requirements. To bring these widely endorsed methods into your training repertoire, Active Training is the complete practical handbook you need.