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Audiobooks by Terrence J. Sejnowski
Browse audiobooks by Terrence J. Sejnowski, listen to samples and when you're ready head over to Audiobooks.com where you can get 3 FREE audiobooks on us
A groundbreaking guide to improve teaching based on the latest research in neuroscience, from the bestselling author of A Mind for Numbers.
Neuroscientists and cognitive scientists have made enormous strides in understanding the brain and how we learn, but little of that insight has filtered down to the way teachers teach. Uncommon Sense Teaching applies this research to the classroom for teachers, parents, and anyone interested in improving education. Topics include:
• keeping students motivated and engaged, especially with online learning
• helping students remember information long-term, so it isn't immediately forgotten after a test
• how to teach inclusively in a diverse classroom where students have a wide range of abilities
Drawing on research findings as well as the authors' combined decades of experience in the classroom, Uncommon Sense Teaching equips readers with the tools to enhance their teaching, whether they're seasoned professionals or parents trying to offer extra support for their children's education.
* This audiobook includes a downloadable PDF of charts and illustrations from the book.
How deep learning-from Google Translate to driverless cars to personal cognitive assistants-is changing our lives and transforming every sector of the economy.
The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.
Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.
