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Modern Deep Learning in Python

Build with modern libraries like Tensorflow, Theano, Keras, PyTorch, CNTK, MXNet. Train faster with GPU on AWS.

Course Summary

Why to enroll this course?

This course continues where my first course, Deep Learning in Python, left off.

If you want to improve your skills with neural networks and deep learning, this is the course for you.

Because you already know about the fundamentals of neural networks, we are going to talk about more modern techniques, like dropout regularization, which we will implement in both TensorFlow and Theano.

In this course we are going to start from the basics so you understand exactly what's going on - what are TensorFlow variables and expressions and how can you use these building blocks to create a neural network?

Because one of the main advantages of TensorFlow and Theano is the ability to use the GPU to speed up training, I will show you how to set up a GPU-instance on AWS and compare the speed of CPU vs GPU for training a deep neural network.

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