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 MLimplementation 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
