Learning-TensorFlow-2.0

A guide to building deep learning systems

This is the code repository for Learning TensorFlow 2.0 [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.

About the Video Course

TensorFlow is one of the most popular Google Deep Learning libraries and has become the industry standard for building AI applications. With the new release of TensorFlow 2.0, its many powerful new features speed up the development process. In this course, we talk about all these new features and paradigms. With our TensorFlow course, you'll master TensorFlow concepts, learn to apply algorithms, and build artificial neural networks—all of these are crucial to Deep Learning and Artificial Intelligence. After you've mastered the new features in TensorFlow 2.0, you'll be able to rapidly build prototypes and move them to production. By the end of this course, you will be able to implement models effectively, easily, and confidently with TensorFlow 2.0.

What You Will Learn

Those who are new to TensorFlow will get an introduction to TensorFlow 1.X so that you appreciate the new features in 2.0
In TensorFlow, you need a special way of writing the code using the Graph Mode and Eager Execution.
Learn complicated concepts such as computation graphs, sessions, placeholders and more.
All the new features that are now introduced in TensorFlow 2.0
With the demo code, you will quickly learn how to apply these new features.
You'll understand how to use Eager Execution in an effective manner
You will learn about the upgrade tool which helps in upgrading your existing TF1.0 code to make it compatible with TF2.0
Learn how image recognition works and how it is implemented using Convolutional Neural Networks and what’s new in TF2.0
How to apply transfer learning and train your network faster with fewer data.
Learn about Recurrent neural networks (RNN) and how they are improved in TF2.0

Instructions and Navigation

Assumed Knowledge

This course is suitable for Deep learning developers and data scientists who want to gain in-depth hands-on knowledge of the newest release of TensorFlow 2.0 and to get into the world of Machine Learning by building as they learn. Some knowledge of Numpy, Pandas, and the Python 3 language is assumed for this course.

Technical Requirements

This course has the following requirements:
Operating system: Windows 7 or Windows 10
Browser: Google Chrome, Latest Version
Code Editor: Atom IDE, Latest Version
Others: Node.js LTS 8.9.1 Installed