Beginning Machine Learning in the Browser : Quick-start Guide to Gait Analysis with JavaScript and TensorFlow.js
Language: English
Published by Apress, 2021
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 46.87
Quantity: 1 available
Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - 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 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. …
Seller Inventory # 9781484268421
- Title
- Beginning Machine Learning in the Browser : Quick-start Guide to Gait Analysis with JavaScript and TensorFlow.js
- Author
- Nagender Kumar Suryadevara
- Publisher
- Apress
- Publication year
- 2021
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1484268423
- ISBN 13
- 9781484268421
- Item weight
- 306 grams
- Dimensions
- 235x155x11 mm
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
"Synopsis" may belong to another edition of this title.
About the Author
"About the title" may belong to another edition of this title.
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