Beginning Machine Learning in the Browser

Beginning Machine Learning in the Browser
  • eBook:
    Beginning Machine Learning in the Browser: Quick-start Guide to Gait Analysis with jаvascript and TensorFlow.js
  • Author:
    Nagender Kumar Suryadevara
  • Edition:
    1 edition
  • Categories:
  • Data:
    May 18, 2021
  • ISBN:
  • ISBN-13:
  • Language:
  • Pages:
    196 pages
  • Format:
    PDF, ePUB

Book Description
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 jаvascript to work with more approachable, fundamental coding ideas. 
Using jаvascript 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


Chapter 1: Web Development
Chapter 2: Browser-Based Data Processing
Chapter 3: Human Pose Estimation in the Browser
Chapter 4: Human Pose Classification
Chapter 5: Gait Analysis
Chapter 6: Future Possibilities for Running AI Methods in a Browser

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