Learning Tensorflow.Js: Powerful Machine Learning in JavaScript

Laborde, Gant

ISBN 10: 1492090794 / ISBN 13: 9781492090793

Verlag: O'Reilly Media (edition 1), 2021

The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way. Bestandsnummer des Verkäufers 1492090794-7-1

Inhaltsangabe:

Given the demand for AI and the ubiquity of JavaScript, TensorFlow.js was inevitable. With this Google framework, seasoned AI veterans and web developers alike can help propel the future of AI-driven websites. In this guide, author Gant Laborde (Google Developer Expert in machine learning and the web) provides a hands-on end-to-end approach to TensorFlow.js fundamentals for a broad technical audience that includes data scientists, engineers, web developers, students, and researchers.

You'll begin by working through some basic examples in TensorFlow.js before diving deeper into neural network architectures, DataFrames, TensorFlow Hub, model conversion, transfer learning, and more. Once you finish this book, you'll know how to build and deploy production-ready deep learning systems with TensorFlow.js.

• Explore tensors, the most fundamental structure of machine learning
• Convert data into tensors and back with a real-world example
• Combine AI with the web using TensorFlow.js
• Use resources to convert, train, and manage machine learning data
• Build and train your own training models from scratch

Über die Autorin bzw. den Autor: Gant Laborde is a proud New Orleans native and adventurous engineer. His accolades include being an owner of Infinite Red, mentor, adjunct professor, published author, and award-winning speaker. As a developer for over 20 years, he has spoken at hundreds of conferences and trained numerous developers. As a Google Developer Expert in both machine learning and the web, he covers TensorFlow.js from multiple perspectives to make the concept approachable. Follow Gant's adventures at http: //gantlaborde.com/

Bibliografische Details

Titel: Learning Tensorflow.Js: Powerful Machine ...
Verlag: O'Reilly Media (edition 1)
Erscheinungsdatum: 2021
Einband: Paperback
Zustand: Fair
Auflage: 1.