Applied Machine Learning for Health and Fitness

1. Front Matter

   Pages i-xvi

   PDF

2. Getting Started

   1. Front Matter

      Pages 1-1

      PDF

   2. Machine Learning in Sports 101

      • Kevin Ashley

      Pages 3-21

   3. Physics of Sports

      • Kevin Ashley

      Pages 23-45

   4. Data Scientist’s Toolbox

      • Kevin Ashley

      Pages 47-72

   5. Neural Networks

      • Kevin Ashley

      Pages 73-91

   6. Sensors

      • Kevin Ashley

      Pages 93-114

3. Applying Machine Learning

   1. Front Matter

      Pages 115-115

      PDF

   2. Deep Computer Vision

      • Kevin Ashley

      Pages 117-135

   3. 2D Body Pose Estimation

      • Kevin Ashley

      Pages 137-159

   4. 3D Pose Estimation

      • Kevin Ashley

      Pages 161-177

   5. Video Action Recognition

      • Kevin Ashley

      Pages 179-197

   6. Reinforcement Learning in Sports

      • Kevin Ashley

      Pages 199-219

   7. Machine Learning in the Cloud

      • Kevin Ashley

      Pages 221-237

   8. Automating and Consuming Machine Learning

      • Kevin Ashley

      Pages 239-252

4. Back Matter

   Pages 253-259

   PDF

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 andmore

Analyze multiple sporting activities with deep learning

Use datasets available today for model training

Use machine learning in the cloud to train and deploy models

Apply 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. 

• Machine Learning
• Sports
• IoT
• Sensors
• Artificial Intelligence
• Virtual Reality
• Python
• R programming
• Unity
• Arduino
• Data scientists
• AI and sports
• AI and fitness
• AI in sport

• Belmont, USA

  Kevin Ashley

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. 

Policies and ethics