© 2020

Applied Machine Learning for Health and Fitness

A Practical Guide to Machine Learning with Deep Vision, Sensors and IoT

  • 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


Table of contents

  1. Front Matter
    Pages i-xvi
  2. Getting Started

    1. Front Matter
      Pages 1-1
    2. Kevin Ashley
      Pages 3-21
    3. Kevin Ashley
      Pages 23-45
    4. Kevin Ashley
      Pages 47-72
    5. Kevin Ashley
      Pages 73-91
    6. Kevin Ashley
      Pages 93-114
  3. Applying Machine Learning

    1. Front Matter
      Pages 115-115
    2. Kevin Ashley
      Pages 117-135
    3. Kevin Ashley
      Pages 137-159
    4. Kevin Ashley
      Pages 161-177
    5. Kevin Ashley
      Pages 179-197
    6. Kevin Ashley
      Pages 199-219
    7. Kevin Ashley
      Pages 221-237
    8. Kevin Ashley
      Pages 239-252
  4. Back Matter
    Pages 253-259

About this book


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.

You will:

  • 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 models
  • Apply best practices in machine learning and data science
  • Keywords

    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

    Authors and affiliations

    1. 1.BelmontUSA

    About the authors

    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. 

    Bibliographic information