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Home Learning Tensorflow.Js: Powerful Machine Learning in JavaScript - Paperback
Learning Tensorflow.Js: Powerful Machine Learning in JavaScript
  • Artificial Intelligence,
  • Books,
  • Computers,
  • Data Science,
  • Machine Learning,
  • Neural Networks,
  • Price Written on Book,

Learning Tensorflow.Js: Powerful Machine Learning in JavaScript - Paperback

Original price $55.99 - Original price $55.99
Original price
$55.99
$55.99 - $55.99
Current price $55.99
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Availability: In Stock
SKU 9781492090793
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by Gant Laborde (Author)

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

Author Biography

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/

Number of Pages: 338
Dimensions: 0.8 x 9.1 x 6.9 IN
Illustrated: Yes
Publication Date: June 15, 2021

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