Beginning Machine Learning in the Browser: Quick-Start Guide to Gait Analysis with JavaScript and Tensorflow.Js

Suryadevara, Nagender Kumar

  • 出版商: Apress
  • 出版日期: 2021-04-02
  • 售價: $1,600
  • 貴賓價: 9.5$1,520
  • 語言: 英文
  • 頁數: 185
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1484268423
  • ISBN-13: 9781484268421
  • 相關分類: JavaScriptDeepLearningTensorFlowMachine Learning
  • 立即出貨 (庫存=1)

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商品描述

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 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

 

商品描述(中文翻譯)

在瀏覽器或資源受限的計算設備上應用人工智慧技術。機器學習(ML)可能是一個令人生畏的主題,直到你了解其基本原理和應用範圍。本書利用ML過程的細節,使用簡單、靈活且可攜的程式語言JavaScript來處理更易理解的基礎編碼概念。

使用JavaScript編程特性和標準庫,您將首先學習設計和開發互動式圖形應用程式。然後深入研究神經系統和人體姿勢估計策略。在瀏覽器中訓練和部署ML模型時,將強調使用TensorFlow.js庫。

掌握基礎知識後,您將進入ML的領域。使用ML和Processing(P5)庫進行人體步態分析。通過主題建立步態識別,您將了解各種ML實現問題。例如,您將學習正常和異常步態模式的分類。

通過《在瀏覽器中開始機器學習》,您將成為一名經驗豐富的機器學習開發人員。

您將學到什麼:

- 使用ML模型、計算和資訊收集
- 實現TensorFlow.js庫的ML模型
- 在瀏覽器中使用ML技術進行人體步態分析

適合閱讀對象:

- 電腦科學學生和研究學者,以及在互聯網技術領域的初學者程式設計師/網頁開發人員

作者簡介

Nagender Kumar Suryadevara received his Ph.D. from the School of Engineering and Advanced Technology, Massey University, New Zealand, in 2014. He has authored two books and over 45 publications in different international journals, conferences, and book chapters. His research interests lie in the domains of wireless sensor networks, Internet of Things technologies, and time-series data mining.

作者簡介(中文翻譯)

Nagender Kumar Suryadevara於2014年從紐西蘭梅西大學工程與先進技術學院獲得博士學位。他撰寫了兩本書籍,並在不同的國際期刊、會議和專書中發表了45篇以上的論文。他的研究興趣涵蓋無線感測網絡、物聯網技術和時間序列數據挖掘等領域。