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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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Applied Machine Learning for Health and Fitness - A Practical Guide to Machine Learning with Deep Vision, Sensors and IoT (Paperback, 1st ed.)
Loot Price: R1,382
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Applied Machine Learning for Health and Fitness - A Practical Guide to Machine Learning with Deep Vision, Sensors and IoT (Paperback, 1st ed.)
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Explore the world of using machine learning methods with deep
computer vision, sensors and data in sports, health and fitness and
other industries. Accompanied by practical step-by-step Python code
samples and Jupyter notebooks, this comprehensive guide acts as a
reference for a data scientist, machine learning practitioner or
anyone interested in AI applications. These ML models and methods
can be used to create solutions for AI enhanced coaching, judging,
athletic performance improvement, movement analysis, simulations,
in motion capture, gaming, cinema production and more. Packed with
fun, practical applications for sports, machine learning models
used in the book include supervised, unsupervised and cutting-edge
reinforcement learning methods and models with popular tools like
PyTorch, Tensorflow, Keras, OpenAI Gym and OpenCV. Author Kevin
Ashley-who happens to be both a machine learning expert and a
professional ski instructor-has written an insightful book that
takes you on a journey of modern sport science and AI. Filled with
thorough, engaging illustrations and dozens of real-life examples,
this book is your next step to understanding the implementation of
AI within the sports world and beyond. Whether you are a data
scientist, a coach, an athlete, or simply a personal fitness
enthusiast excited about connecting your findings with AI methods,
the author's practical expertise in both tech and sports is an
undeniable asset for your learning process. Today's data scientists
are the future of athletics, and Applied Machine Learning for
Health and Fitness hands you the knowledge you need to stay
relevant in this rapidly growing space. What You'll Learn Use
multiple data science tools and frameworks Apply deep computer
vision and other machine learning methods for classification,
semantic segmentation, and action recognition Build and train
neural networks, reinforcement learning models and more Analyze
multiple sporting activities with deep learning Use datasets
available today for model training Use machine learning in the
cloud to train and deploy modelsApply best practices in machine
learning and data science Who This Book Is For Primarily aimed at
data scientists, coaches, sports enthusiasts and athletes
interested in connecting sports with technology and AI methods.
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