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Beginning Machine Learning in the Browser

Quick-start Guide to Gait Analysis with JavaScript and TensorFlow.js

Language EnglishEnglish
E-book Adobe ePub DRM
Publishers Apress, April 2021
Apply Artificial Intelligence techniques in the browser or on resource constrained computing devices... Full description
? points 131 b
54.29
In stock Immediate digital delivery


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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 LearnWork with ML models, calculations, and information gatheringImplement TensorFlow.js libraries for ML modelsPerform Human Gait Analysis using ML techniques in the browserWho This Book Is ForComputer science students and research scholars, and novice programmers/web developers in the domain of Internet Technologies

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About the book

Full name Beginning Machine Learning in the Browser
Language English
Binding E-book - Adobe ePub DRM
Date of issue 2021
EAN 9781484268438
Libristo code 40410947
Publishers Apress
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