Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
What's New in TensorFlow 2.0

You're reading from   What's New in TensorFlow 2.0 Use the new and improved features of TensorFlow to enhance machine learning and deep learning

Arrow left icon
Product type Paperback
Published in Aug 2019
Publisher Packt
ISBN-13 9781838823856
Length 202 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (3):
Arrow left icon
Tanish Baranwal Tanish Baranwal
Author Profile Icon Tanish Baranwal
Tanish Baranwal
Alizishaan Khatri Alizishaan Khatri
Author Profile Icon Alizishaan Khatri
Alizishaan Khatri
Ajay Baranwal Ajay Baranwal
Author Profile Icon Ajay Baranwal
Ajay Baranwal
Arrow right icon
View More author details
Toc

Table of Contents (13) Chapters Close

Preface 1. Section 1: TensorFlow 2.0 - Architecture and API Changes
2. Getting Started with TensorFlow 2.0 FREE CHAPTER 3. Keras Default Integration and Eager Execution 4. Section 2: TensorFlow 2.0 - Data and Model Training Pipelines
5. Designing and Constructing Input Data Pipelines 6. Model Training and Use of TensorBoard 7. Section 3: TensorFlow 2.0 - Model Inference and Deployment and AIY
8. Model Inference Pipelines - Multi-platform Deployments 9. AIY Projects and TensorFlow Lite 10. Section 4: TensorFlow 2.0 - Migration, Summary
11. Migrating From TensorFlow 1.x to 2.0 12. Other Books You May Enjoy

New abstractions in TF 2.0

Abstractions are a very popular tool used in the process of programming and software development. In a very high-level sense, an abstraction refers to the process of isolating and describing the central idea of a particular task or set of tasks without necessarily specifying the physical, spatial, or temporal details. When done right, an abstraction can significantly reduce the amount of code that needs to be written for a particular task. It also boosts the reusability of existing code and makes it compatible with TF 2.0.

While working with machine learning systems, there are some common high-level tasks, such as training data, modeling, model evaluation, prediction, model storing, and model loading, that are common across a wide variety of tasks. An end programmer might also want to just modify one small component of the application while leaving the...

You have been reading a chapter from
What's New in TensorFlow 2.0
Published in: Aug 2019
Publisher: Packt
ISBN-13: 9781838823856
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime