All neural networks architectures lay on the same principles. There are neurons with biases and activation functions connected with weighted connections. However, different problems require the different mix of those neurons and connections. That is how we ended up with…

## Generate Music Using TensorFlow and Python

Not many people know, but apart from doing all techy stuff, I sometimes make music. I even have few EP releases and one album. They are terrible, but hey, it is something to pass the time. Anyhow, after getting deeper…

## Stock Price Prediction Using Hidden Markov Model

Learn to predict stock prices using HMM in this article by Ankur Ankan, an open source enthusiast, and Abinash Panda, a data scientist who has worked at multiple start-ups. A Hidden Markov Model (HMM) is a specific case of the state space…

## Implementing Restricted Boltzmann Machine with Python and TensorFlow

In one of the previous articles, we started learning about Restricted Boltzmann Machine. It was quite a journey since we first had to figure out what energy-based models are, and then to find out how a standard Boltzmann Machine functions.…

## 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…

## 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…

## 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…

## Self- Organizing Maps Series

So far in our artificial neural network series, we have covered only neural networks that are using supervised learning. To be more precise, we only explored neural networks that have input and output data available to them during the learning process. Based…

## Credit Card Fraud Detection Using Self-Organizing Maps and Python

In the previous three articles, we explored the world of Self-Organizing Maps. First, we got some theoretical background on the subject. Then in the second article, we saw how we could implement Self-Organizing Maps using TensorFlow. After that, in the…

## 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…