Practical Machine Learning in JavaScript: TensorFlow.js for Web Developers
Author:   Charlie Gerard
Publisher:   APress
Edition:   1st ed.
ISBN:  

9781484264171


Pages:   323
Publication Date:   17 November 2020
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Practical Machine Learning in JavaScript: TensorFlow.js for Web Developers


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Author:   Charlie Gerard
Publisher:   APress
Imprint:   APress
Edition:   1st ed.
Weight:   0.522kg
ISBN:  

9781484264171


ISBN 10:   1484264177
Pages:   323
Publication Date:   17 November 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Chapter 1: Introduction to Machine Learning •   Definition •   Explanation of concepts •   Algorithms •   Examples of impact Chapter 2: Basics of Tensorflow.js •   What is Tensorflow.js? •   Features Chapter 3: Building an Image Classifier •   Using a pre-trained model •   Creating a custom model •   Saving and loading a model Chapter 4: Building a Sentiment Analysis System •   Train a model with text data •   Create text-based ML applications Chapter 5: Experimenting with Inputs •   Using ML with electronics data •   Using audio data Chapter 6: Deploying Models Chapter7: Ethics in AI

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Author Information

Charlie Gerard is a Senior front-end developer at Netlify, a Google Developer Expert in Web Technologies, and a Mozilla Tech Speaker. She is passionate about exploring the possibilities of the web and spends her personal time building interactive prototypes using hardware, creative coding, and machine learning. She has been diving into ML in JavaScript for over a year and built a variety of projects. She’s excited to share what she’s learned and help more developers get started.

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