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The publisher makes no warranty, express or implied, with respect to the material contained herein. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Rather than use a trademark symbol with every occurrence of a trademarked name, logo, or image we use the names, logos, and images only in an editorial fashion and to the benefit of the trademark owner, with no intention of infringement of the trademark. Trademarked names, logos, and images may appear in this book. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Practical Machine Learning in JavaScript: TensorFlow.js for Web Developers Charlie Gerard Les Clayes sous bois, France ISBN-13 (pbk): 978-1-4842-6417-1 Ĭopyright © 2021 by Charlie Gerard This work is subject to copyright. Practical Machine Learning in JavaScript TensorFlow.js for Web Developers Practical Machine Learning in JavaScript TensorFlow.js for Web Developers - Charlie Gerard
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Machine learning in production (Charlie Gerard).Pages 287-303īias in machine learning (Charlie Gerard).Pages 305-316īack Matter. Text classification and sentiment analysis (Charlie Gerard).Pages 67-134Įxperimenting with inputs (Charlie Gerard).Pages 135-286 TensorFlow.js (Charlie Gerard).Pages 25-43īuilding an image classifier (Charlie Gerard).Pages 45-66 The basics of machine learning (Charlie Gerard).Pages 1-24