國立虎尾科技大學 |

Beginning Machine Learning in the Browser = Quick-start Guide to Gait Analysis with JavaScript and TensorFlow.js /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Beginning Machine Learning in the Browser/ by Nagender Kumar Suryadevara.
其他題名:	Quick-start Guide to Gait Analysis with JavaScript and TensorFlow.js /
作者:	Suryadevara, Nagender Kumar.
面頁冊數:	XIV, 182 p. 71 illus.online resource. :
Contained By:	Springer Nature eBook
標題:	Artificial Intelligence. -
電子資源:	https://doi.org/10.1007/978-1-4842-6843-8
ISBN:	9781484268438

Beginning Machine Learning in the Browser = Quick-start Guide to Gait Analysis with JavaScript and TensorFlow.js /
Suryadevara, Nagender Kumar.

Beginning Machine Learning in the BrowserQuick-start Guide to Gait Analysis with JavaScript and TensorFlow.js /[electronic resource] :by Nagender Kumar Suryadevara. - 1st ed. 2021. - XIV, 182 p. 71 illus.online resource.

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

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. You will: 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.

ISBN: 9781484268438

Standard No.: 10.1007/978-1-4842-6843-8doiSubjects--Topical Terms:

646849
Artificial Intelligence.

LC Class. No.: Q334-342

Dewey Class. No.: 006.3

Beginning Machine Learning in the Browser = Quick-start Guide to Gait Analysis with JavaScript and TensorFlow.js /
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