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Hands-On Deep Learning with TensorFlow 2.0

Video Description

Your hands-on guide Deep Learning to get you up and running with TensorFlow 2.0, more effectively than other courses!

About This Video

  • Understand the complexities of open source library and deep learning with ease and with code implementation in Python.
  • We follow the PEP8 rules for the code implementation which keep you au fait with coding standards and updated tools and techniques like Jupyter notebook and Tensorflow 2.0
  • As Tensorflow 2.0 is in a development Phase so it will cover the most updated content throughout this course.

In Detail

Are you eager to deep dive into the details of neural networks and would like to play with it? Do you want to learn Deep Learning Techniques to build projects with the latest Tensorflow 2.0. You may use Keras but it is a high-level implementation which itself uses Tensorflow in the backend and you can’t make changes up to that level in your model as of TensorflowKeras. A good data scientist must have the skill of how things are going on behind the scenes.

This course will help you to be a good Data Scientist by giving hands-on knowledge of Tensorflow 2.0. You will implement real deep learning algorithms and will be available with all the implementation. Using implementation you will learn core details of a neural network like forward-propagation i.e, how to initialize weights and backpropagation i.e, how to update weights with gradient descent algorithm, Cost functions like cross entropy and much more.

By the end of this course, you will be confident to implement your own neural network that is a very amazing thing you are adding to your toolbox.

All the code and supporting files for this course are available on GitHub at https://github.com/PacktPublishing/Hands-on-Deep-Learning-with-TensorFlow-2.0

Downloading the example code for this course: You can download the example code files for all Packt video courses you have purchased from your account at http://www.PacktPub.com. If you purchased this course elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.