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…

0 comments on “Machine Learning to Catch Up with Human Intelligence – The Outcome”

Machine Learning to Catch Up with Human Intelligence – The Outcome

With our dependence on technology only becoming stronger and with some recent privacy-destroyed scandals making people worry, robots became the talk of the town once again. Almost every film, TV show, and video game tries to raise a question about…

2 comments on “Implementing Restricted Boltzmann Machine with .NET Core”

Implementing Restricted Boltzmann Machine with .NET Core

The code that accompanies this article can be downloaded here. In the previous article, we had a chance to see what is the Restricted Boltzmann Machine and how it functions and learns. The path was bumpy because first, we needed to…

2 comments on “Introduction to Restricted Boltzmann Machines”

Introduction to Restricted Boltzmann Machines

So far in our artificial neural network journey, we have explored typical statistical models. In general, the entire point of statistical modeling and machine learning is to detect dependencies and connections between input variables. Standard Neural networks are exceptional at…

2 comments on “Implementing Self-Organizing Maps with .NET Core”

Implementing Self-Organizing Maps with .NET Core

The code that accompanies this article can be downloaded here. In the previous articles, we explored what  Self-Organizing Maps are and how you can implement them using Python and TensorFlow. One of the most interesting things about these networks is that…