2 comments on “Introduction to Tensorflow.js with Real-World Example”

Introduction to Tensorflow.js with Real-World Example

The code that accompanies this article can be downloaded here. Open-source library TensorFlow.js was introduced about a year ago. However, I didn't manage to try it out up until now. In this article, we are going to get to know how…

1 comment on “AutoML and the Rise of Advanced Machine Learning Platforms”

AutoML and the Rise of Advanced Machine Learning Platforms

People are yet not done figuring out machine learning, and now there is a rise of a new advanced term on the market for machine learning, and, i.e. “Automated Machine Learning.”  Let’s discuss automated machine learning. Thankfully, automated machine learning…

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).