English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 1h 29m | 488 MB
Understanding TensorFlow 2.0’s new features
TensorFlow is a popular and widely-adopted open-source Machine Learning library. It is Python-friendly and used in various AI areas such as deep learning, numeric computation, and large-scale Machine Learning. The newest version of TensorFlow includes major highlights such as improved eager execution, improved compatibility, support for major platforms and languages, and more; it also removes deprecated APIs. The new features will make TensorFlow easier to learn and apply.
In this course, you will cover all of the new features that have been introduced in TensorFlow 2.0 especially the major highlight including Eager Execution and more. You will learn how to make the best use of these features and how it improves and simplifies the way you use TensorFlow.
By the end of the course, you will have an understanding of the new features introduced in TensorFlow 2.0 and will be able to apply them in your work.
This is an introductory course specially designed for programmers who are already working with the older version of TensorFlow and want to explore the new features in TensorFlow 2.0. Every module includes an illustration to help you understand concepts in depth and execute them in real-world case studies.
What You Will Learn
- Focus mainly on the new features of TensorFlow 2.0 launched in Jan 2019.
- Easy model building with TensorFlow and eager execution.
- Robust model deployment in production on any platform.
- Powerful experimentation for research.
- Simplify your API by cleaning up deprecated APIs and reducing duplication.