English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 4h 08m | 855 MB
Learn to use Google’s framework: TensorFlow 2.0
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.
This step-by-step course is specially designed for beginners, with a lot of code demos and code templates to get you started very quickly. The new features are explained briefly with a few slides and then we go straight into Jupyter Notebook to show an appropriate code example of how each new feature works.
Watch the code demo video first without trying to do the hands-on, so that you’re not distracted. Then re-run the video and at the same time run the code in your development environment. Pause the video as appropriate to understand the explanation of what a particular line of code is or what a code snippet is doing. Make a copy of the file and play around by tweaking some parameters to see what happens. This is the best way to learn; don’t worry about breaking the code!
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