Price: $11.99
(as of Dec 04,2024 21:54:05 UTC – Details)

From the brand

Explore our collection

Sharing the knowledge of experts

O’Reilly’s mission is to change the world by sharing the knowledge of innovators. For over 40 years, we’ve inspired companies and individuals to do new things (and do them better) by providing the skills and understanding that are necessary for success.

Our customers are hungry to build the innovations that propel the world forward. And we help them do just that.

ASIN ‏ : ‎ B074PDHDQQ
Publisher ‏ : ‎ O’Reilly Media; 1st edition (August 9, 2017)
Publication date ‏ : ‎ August 9, 2017
Language ‏ : ‎ English
File size ‏ : ‎ 10360 KB
Simultaneous device usage ‏ : ‎ Unlimited
Text-to-Speech ‏ : ‎ Enabled
Screen Reader ‏ : ‎ Supported
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 414 pages

Learning TensorFlow: A Guide to Building Deep Learning Systems

Are you interested in diving into the world of deep learning and building powerful machine learning models? Look no further than TensorFlow. As one of the most popular deep learning frameworks, TensorFlow provides a comprehensive set of tools for building and training neural networks.

In this guide, we will walk you through the basics of TensorFlow and show you how to start building your own deep learning systems. From setting up your environment to creating and training your first neural network, we will cover everything you need to know to get started with TensorFlow.

Whether you are a beginner looking to learn the fundamentals of deep learning or an experienced data scientist wanting to expand your skillset, this guide will provide you with the knowledge and resources to build sophisticated deep learning models using TensorFlow.

Stay tuned for our upcoming posts where we will delve deeper into advanced topics such as convolutional neural networks, recurrent neural networks, and more. Get ready to unlock the potential of deep learning with TensorFlow.
#Learning #TensorFlow #Guide #Building #Deep #Learning #Systems