Apply Artificial Intelligence techniques in the browser or on resource
constrained computing devices. Machine learning (ML) can be an
intimidating subject until you know the essentials and for what
applications it works. This book takes advantage of the intricacies of
the ML processes by using a simple, flexible and portable programming
language such as JavaScript to work with more approachable, fundamental
coding ideas.
Using JavaScript programming features along with standard libraries,
you'll first learn to design and develop interactive graphics
applications. Then move further into neural systems and human pose
estimation strategies. For training and deploying your ML models in the
browser, TensorFlow.js libraries will be emphasized.
After conquering the fundamentals, you'll dig into the wilderness of ML.
Employ the ML and Processing (P5) libraries for Human Gait analysis.
Building up Gait recognition with themes, you'll come to understand a
variety of ML implementation issues. For example, you'll learn about the
classification of normal and abnormal Gait patterns.
With Beginning Machine Learning in the Browser, you'll be on your way
to becoming an experienced Machine Learning developer.
What You'll Learn
- Work with ML models, calculations, and information gathering
- Implement TensorFlow.js libraries for ML models
- Perform Human Gait Analysis using ML techniques in the browser
Who This Book Is For
Computer science students and research scholars, and novice
programmers/web developers in the domain of Internet Technologies
