Applied Machine Learning for Health and Fitness

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 Ashleywho happens to be both a machine learning expert and a professional ski instructorhas 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 LearnUse multiple data science tools and frameworksApply deep computer vision and other machine learning methods for classification, semantic segmentation, and action recognitionBuild and train neural networks, reinforcement learning models andmoreAnalyze multiple sporting activities with deep learningUse datasets available today for model trainingUse machine learning in the cloud to train and deploy modelsApply best practices in machine learning and data scienceWho This Book Is ForPrimarily aimed at data scientists, coaches, sports enthusiasts and athletes interested in connecting sports with technology and AI methods.

Demonstrates machine learning models with real-world use cases Build your own IoT devices and sensors for athletes Covers examples of data visualization through holograms and VR

Auteur

Kevin Ashley is a Microsoft architect, IoT expert, and professional ski instructor. He is an author and developer of top sports and fitness apps and platforms such as Active Fitness and Winter Sports with a multi-million user audience. Kevin often works with sports scientists, Olympic athletes, coaches and teams to advance technology use in sports.

Contenu

Part I: Getting Started.- Chapter 1: Machine Learning in Sports 101.- Chapter 2: Physics of Sports.- Chapter 3: Data Scientist's Toolbox.- Chapter 4: 3D Neutral Networks.- Chapter 5: Sensors.- Part 2: Applied Machine Learning.- Chapter 6: Deep Computer Learning.- Chapter 7: 2D Body Pose Estimation.- Chapter 8: 3D Pose Estimation.- Chapter 9: Video Action Recognition.- Chapter 10: Reinforcement Learning in Sports.- Chapter 11: Machine Learning in the Cloud.- Chapter 12: Automating and Consuming Machine Learning.