1 comment on “Drawing with Voice – Speech Recognition with TensorFlow.js”

Drawing with Voice – Speech Recognition with TensorFlow.js

When I was a kid every almost every superhero had a voice-controlled computer. So you can imagine how my first encounter with Alexa was a profound experience for me. The kid in me was so happy and excited. Of course, then my engineering instincts kicked in and I analyzed how these devices work. Turned out they have neural networks that handle this complicated problem.

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).

2 comments on “Introduction to Adversarial Autoencoders”

Introduction to Adversarial Autoencoders

Generative Adversarial Networks (GAN) shook up the deep learning world. When they first appeared in 2014, they proposed a new and fresh approach to modeling and gave a possibility for new neural network architectures to emerge. Since standard GAN architecture is composed of two neural networks, we can play around and use different approaches for those networks and thus create new and shiny architectures, like Adversarial Autoencoder.

0 comments on “3 Ways to Implement Autoencoders with TensorFlow and Python”

3 Ways to Implement Autoencoders with TensorFlow and Python

In one of the previous articles, we started our journey into the world of Autoencoders. We saw that they are one special kind of neural networks, that was able to utilize techniques of supervised learning for unsupervised learning. One might…