1 comment on “Deep Q-Learning with Python and TensorFlow 2.0”

Deep Q-Learning with Python and TensorFlow 2.0

In the previous two articles we started exploring the interesting universe of reinforcement learning. First we went through the basics of third paradigm within machine learning - reinforcement learning. Just to freshen up our memory, we saw that approach of…

0 comments on “5 Reasons Why Python Is Popular in Bitcoin Projects in 2019”

5 Reasons Why Python Is Popular in Bitcoin Projects in 2019

This is a guest post by Kateryna Boiko. Bitcoin is one of the pioneer cryptocurrency in the world. It has changed the financial landscape across the globe. A huge majority of the people dealing in trade and financing are showing…

0 comments on “Generating Images using Adversarial Autoencoders and Python”

Generating Images using Adversarial Autoencoders and Python

When they were first presented back in 2014., Generative Adversarial Networks (GAN) took the world of Deep Learning by storm. Their two folded architecture opened up the path to many creative solutions and combinations. Even Yann LeCun concluded that this is “the most interesting idea in the last 10 years in Machine Learning”.  Since then, GAN zoo grew a lot. New architectures that harvest this adversarial premise are created on a regular basis. One of those solutions is Adversarial Autoencoders (AAE).