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

Comparing Keras and tf.keras

tf.keras is TensorFlow's implementation of the Keras API specification. This is a high-level API to build and train models, which includes first-class support for TensorFlow-specific functionality, such as eager execution, tf.data pipelines, and estimators. tf.keras makes TensorFlow easier to use without sacrificing flexibility and performance.

Keras (the original website that defines the Keras API standard) has been an open source project that got tremendous attention from ML engineers and data scientists due to its simplicity and strength. Initially, the default backend engine for Keras (remember, Keras is a set of APIs) was Theano; however, lately, it has changed, with TensorFlow now as its default backend engine. You can also set the default backend engine to MXNet, CNTK, and so on. Keras APIs are extremely user-friendly, modular, and composable...

lock icon The rest of the chapter is locked
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