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Ajouter au panierPaperback. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 0.63.
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Ajouter au panierPaperback or Softback. Etat : New. Beginning Machine Learning in the Browser: Quick-Start Guide to Gait Analysis with JavaScript and Tensorflow.Js. Book.
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Ajouter au panierEtat : New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books!
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
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Ajouter au panierPaperback. Etat : New. 1st ed. 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.
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
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Ajouter au panierPaperback / softback. Etat : New. New copy - Usually dispatched within 2 working days. 184.
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Ajouter au panierPaperback. Etat : Brand New. 182 pages. 9.00x6.00x0.50 inches. In Stock.
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Ajouter au panierEtat : New. 2021. Paperback. . . . . . Books ship from the US and Ireland.
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Ajouter au panierEtat : New. In English.
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Ajouter au panierEtat : New. 1st ed. edition NO-PA16APR2015-KAP.
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Ajouter au panierEtat : New. Perform human gait analysis with TensorFlow.JS ML and Processing (P5) librariesBuild a solid foundation in machine learning with the ubiquitous JavaScript languageTrain and deploy ML models in the browser with TensorFlow.jsNagen.
Vendeur : Rarewaves.com UK, London, Royaume-Uni
Edition originale
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Ajouter au panierPaperback. Etat : New. 1st ed. 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.
Edité par Apress, Apress Apr 2021, 2021
ISBN 10 : 1484268423 ISBN 13 : 9781484268421
Langue: anglais
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Ajouter au panierTaschenbuch. Etat : Neu. Neuware -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, yoüll learn about the classification of normal and abnormal Gait patterns.With Beginning Machine Learning in the Browser, yoüll be on your way to becoming an experienced Machine Learning developer.What Yoüll 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 TechnologiesAPress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 196 pp. Englisch.
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Ajouter au panierTaschenbuch. Etat : Neu. Beginning Machine Learning in the Browser | Quick-start Guide to Gait Analysis with JavaScript and [.] | Nagender Kumar Suryadevara | Taschenbuch | xiv | Englisch | 2021 | APRESS | EAN 9781484268421 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 196 pp. Englisch.
Vendeur : Majestic Books, Hounslow, Royaume-Uni
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Ajouter au panierTaschenbuch. Etat : Neu. 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.