Normal position et al.: Google Deep Learning Framework: TensorFlow in Practice

In recent years, news, blogs and so on, we have the word Deeping. For decades, artificial intelligence technology has been constantly developing, but science and industry technology like Deeping has been in trouble for 10 years. The sad thing is that it's hard to understand and apply deep-diving, especially with complex mathematical models, to give up on students who are not as few. And to make matters worse, deep-diving technology has made rapid progress, and writing and publishing processes are so complex that it's hard to find books that describe the process of deep-downing. And even more so is the most popular deep-ing framework on the EnsorFame. That's why he wrote this book through the night. As an IT worker and founder, I hope you can use this book to help you learn deep-downs quickly with examples of code and not complicated mathematical formulas. In early '20, he and some friends resigned from Google, U.S.A., and returned to Hangau to give companies AI platform and solution to the free economy. We've co-founded o'. By the time he came to China, many companies had already been very interested in the EnsorFame. But after a deep conversation with these people, he found that despite the fact that EnsorFeven was a very easy tool to use, not all companies at the time could really use Deeping technology. So he started writing this book so that more individuals and companies could benefit from deep-running technology.

Korean title: 구글 딥러닝 프레임워크: 텐서플로우 실전

Korean author: 정저위 외

Korean publisher: 광문각

ISBN-13: 9788970939445