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Written by Chuck Easttom, “Machine Learning for Neuroscience: A Systematic Approach” is a pioneering book that addresses the growing need for machine learning and data mining in neuroscience. This book provides a thorough understanding of the essential concepts in neuroscience, machine learning, and the required math and programming skills to develop reliable working models.
The book is designed to be user-friendly, making it accessible to neuroscience researchers and practitioners with little to no training in machine learning. The material is presented in an easy-to-follow manner, replete with fully working machine learning code examples and downloadable working code.
The first section of the book covers the necessary topics to delve into machine learning, including:
The second section provides an overview of neuroscience, directed towards computer science-oriented readers, covering:
The third section of the book dives into the application of machine learning and data mining to neuroscience, including:
The book also includes lab assignments and quizzes, making it an ideal textbook for students studying methods in computational neuroscience.
The primary audience for this book includes:
Published by CRC Press, this book is a valuable resource for anyone looking to leverage machine learning and data mining in neuroscience. With its comprehensive coverage and user-friendly approach, it is an essential guide for professionals and students alike.
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