TensorFlow 2.0 brings a lot of changes. Google engineer Cassie Kozyrkov said that the previous TensorFlow was dead, and the new version of TensorFlow made it reborn.
"Free" Wu Enda's new course "TensorFlow: From Getting Started to Proficient"
TensorFlow: Getting Started to Mastering is a series of practical courses at Deeplearning.ai, developed and coached by Wu Enda. In addition to Teacher Wu Enda, another heavyweight teacher of the course is Dr. Laurence Moroney.
About TensorFlow, you should know the 9 key points
TensorFlow is a powerful machine learning framework. This article introduces 9 features about TensorFlow, primarily for technicians and non-technical people who want to learn about TensorFlow. At the same time, this article also contains a lot of useful resources to help you understand and learn more comprehensively.
Fun with TensorFlow? You need to know this 30 feature
Paige Bailey (@DynamicWebPaige), a Google AI engineer and active advertiser of Google AI, summarizes the key features of TensorFlow's 30.
A detailed explanation of TensorFlow 2.0's symbolic API and imperative API
Josh Gordon posted a blog on the TensorFlow website detailing the symbolic API and the imperative API, detailing the strengths and limitations of each of the two styles, and which ones are applicable to each. Scenes.
BAT expert interpretation: How to choose the most appropriate deep learning framework?
With deep learning attention and momentum, deep learning is being combined with the production practices of more and more companies and organizations. At this time, whether it is for beginners of deep learning related majors or developers who have been engaged in industrial scene application and R&D in enterprises and organizations, it is particularly important to choose a deep learning framework that suits their needs and suits the needs of business scenarios.
[Official release] A picture to understand the new architecture of TensorFlow 2.0
As an important milestone, TensorFlow 2.0 will pay more attention to its "ease of use" and pay more attention to the low threshold of use, aiming to enable everyone to apply machine learning technology.