Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and biologically-inspired techniques. Mariette Awad and Rahul Khanna’s synthetic approach weaves together the theoretical exposition, design principles, and practical applications of efficient machine learning. Their experiential emphasis, expressed in their close analysis of sample algorithms throughout the book, aims to equip engineers, students of engineering, and system designers to design and create new and more efficient machine learning systems. Readers of Efficient Learning Machines will learn how to recognize and analyze the problems that machine learning technology can solve for them, how to implement and deploy standard solutions to sample problems, and how to design new systems and solutions. Advances in computing performance, storage, memory, unstructured information retrieval, and cloud computing have coevolved with a new generation of machine learning paradigms and big data analytics, which the authors present in the conceptual context of their traditional precursors. Awad and Khanna explore current developments in the deep learning techniques of deep neural networks, hierarchical temporal memory, and cortical algorithms. Nature suggests sophisticated learning techniques that deploy simple rules to generate highly intelligent and organized behaviors with adaptive, evolutionary, and distributed properties. The authors examine the most popular biologically-inspired algorithms, together with a sample application to distributed datacenter management. They also discuss machine learning techniques for addressing problems of multi-objective optimization in which solutions in real-world systems are constrained and evaluated based on how well they perform with respect to multiple objectives in aggregate. Two chapters on support vector machines and their extensions focus on recent improvements to the classification and regression techniques at the core of machine learning.

Efficiency in Learning offers a road map of the most effective ways to use the three fundamental communication of training: visuals, written text, and audio. Regardless of how you are delivering your training materials—in the classroom, in print, by synchronous or asynchronous media—the book’s methods are easily applied to your lesson presentations, handouts, reference guides, or e-learning screens. Designed to be a down-to-earth resource for all instructional professionals, Efficiency in Learning’s guidelines are clearly illustrated with real-world examples.

"Large-scale efforts have been made since the 1990s to ensure that all children of the world go to school. But mere enrollment is not sufficient, students must become fluent in reading and calculation by the end of grade 2. Fluency is needed to process large amounts of text quickly and use the information for decisions that may ultimately reduce poverty. State-of-the-art brain imaging and cognitive psychology research can help formulate effective policies for improving the basic skills of low-income students. This book integrates research into applications that extend from preschool brain development to the memory of adult educators. In layman?'s terms, it provides explanations and answers to questions such as: Why do children have to read fast before they can understand what they read? How do health, nutrition, and stimulation influence brain development? Why should students learn basic skills in their maternal language? Is there such a thing as an untrained teacher? What signs in a classroom show whether students are getting a quality education? How must information be presented in class so that students can retain it and use it? What training techniques are most likely to help staff put their learning into use? This book would be useful to policymakers, donor agency staff, teacher trainers, supervisors, and inspectors, as well as university professors and students."

This publication offers and investigates efficient Monte Carlo simulation methods in order to realize a Bayesian approach to approximate learning of Bayesian networks from both complete and incomplete data. For large amounts of incomplete data when Monte Carlo methods are inefficient, approximations are implemented, such that learning remains feasible, albeit non-Bayesian. The topics discussed are: basic concepts about probabilities, graph theory and conditional independence; Bayesian network learning from data; Monte Carlo simulation techniques; and, the concept of incomplete data. In order t.

Explicit instruction is systematic, direct, engaging, and success oriented--and has been shown to promote achievement for all students. This highly practical and accessible resource gives special and general education teachers the tools to implement explicit instruction in any grade level or content area. The authors are leading experts who provide clear guidelines for identifying key concepts, skills, and routines to teach; designing and delivering effective lessons; and giving students opportunities to practice and master new material. Sample lesson plans, lively examples, and reproducible checklists and teacher worksheets enhance the utility of the volume. Purchasers can also download and print the reproducible materials for repeated use. Video clips demonstrating the approach in real classrooms are available at the authors' website: www.explicitinstruction.org. See also related DVDs from Anita Archer: Golden Principles of Explicit Instruction; Active Participation: Getting Them All Engaged, Elementary Level; and Active Participation: Getting Them All Engaged, Secondary Level

For a young person to have a successful career at school and become a lifelong learner it is essential that they develop the skills to learn effectively. This timely book looks at ways in which teachers can identify and deal with barriers to learning and suggests strategies which motivate young people to develop an interest in their own learning.

Primary languages are to be an entitlement for all pupils in KS2 from 2010. There is therefore a need to ensure that trainee primary teachers are equipped with the required skills, knowledge and understanding to contribute to this process. This book supports specialists, and also non-specialist trainees with an interest in MFL, who may need to deliver languages across the curriculum, providing them with a clear understanding of the methodology and helping them to develop linguistic competence and confidence.