The exciting adventures of Ebony Smart, a twelve-year-old girl who discovers she is part of a special tribe of reincarnated people – and a terrible curse. Ebony has just one week to break the curse or die; if she fails, the future of her family, and her people, is at risk – does she have what it takes to succeed? • A magical story with an Irish setting for readers aged 9–12 years; appeals to both boys and girls • An exciting fantasy adventure from the publishers of the Arthur Quinn series • An active and respected author After the death of her beloved grandfather on her twelfth birthday, Ebony Smart's world is turned upside down. Orphaned for a second time, she is sent to Dublin to live with her weird Aunt Ruby, with only her pet rat, Winston, for company. With every window nailed shut and a mysterious locked room, 23 Mercury Lane is brimming with secrets. Warned against entering by a voice in the shadows, Ebony is fearful for her future, but has no idea how much her life is about to change. Aunt Ruby informs Ebony that she is part of the Order of Nine Lives – a special tribe of people who reincarnate. She claims Ebony has one week to break a terrible curse or else die – and if she fails, the future of the Order of Nine Lives, and her family, is at risk. With so much at stake, Ebony discovers it's difficult to trust – especially when there's somebody else trying to race her to the finish. Does she have what it takes to succeed when nothing is what it seems?

In this thought-provoking book, Frank Smith explains how schools and educational authorities systematically obstruct the powerful inherent learning abilities of children, creating handicaps that often persist through life. The author eloquently contrasts a false and fabricated “official theory” that learning is work (used to justify the external control of teachers and students through excessive regulation and massive testing) with a correct but officially suppressed “classic view” that learning is a social process that can occur naturally and continually through collaborative activities. This book will be crucial reading in a time when national authorities continue to blame teachers and students for alleged failures in education. It will help educators and parents to combat sterile attitudes toward teaching and learning and prevent current practices from doing further harm.

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.

An eight-time national chess champion and world champion martial artist shares the lessons he has learned from two very different competitive arenas, identifying key principles about learning and performance that readers can apply to their life goals. Reprint. 35,000 first printing.

Like the first edition, the second edition of Learning by Doing: A Handbook for Professional Learning Communities at Work helps educators close the knowing-doing gap as they transform their schools into professional learning communities (PLCs).

Essays by popular children's authors reveal the books that shaped their personal and literary lives, explaining how the stories they loved influenced them creatively, politically, and intellectually.

Educational practice does not, for the most part, rely on research findings. Instead, there’s a preference for relying on our intuitions about what’s best for learning. But relying on intuition may be a bad idea for teachers and learners alike. This accessible guide helps teachers to integrate effective, research-backed strategies for learning into their classroom practice. The book explores exactly what constitutes good evidence for effective learning and teaching strategies, how to make evidence-based judgments instead of relying on intuition, and how to apply findings from cognitive psychology directly to the classroom. Including real-life examples and case studies, FAQs, and a wealth of engaging illustrations to explain complex concepts and emphasize key points, the book is divided into four parts: Evidence-based education and the science of learning Basics of human cognitive processes Strategies for effective learning Tips for students, teachers, and parents. Written by "The Learning Scientists" and fully illustrated by Oliver Caviglioli, Understanding How We Learn is a rejuvenating and fresh examination of cognitive psychology's application to education. This is an essential read for all teachers and educational practitioners, designed to convey the concepts of research to the reality of a teacher's classroom.