Backpropagation is the key algorithm that makes training deep models computationally tractable. For modern neural networks, it can make training with gradient descent as much as ten million times faster, relative to a naive implementation. That’s the …
This has really been quite a journey for me lately. And regarding the frequently asked question “Why did you choose Python for Machine Learning?” I guess it…
The new version of Datumbox Machine Learning Framework has been released! Download it now from Github or Maven Central Repository. What is new? The main focus of version 0.6.0 is to extend the Framework to handle Large Data, improve the code architectu…
This article offers a brief glimpse of the history and basic concepts of machine learning. We will take a look at the first algorithmically described neural…
Principal Component Analysis (PCA) is a simple yet popular and useful linear transformation technique that is used in numerous applications, such as stock…
In a previous post, we explored techniques for visualizing high-dimensional data. Trying to visualize high dimensional data is, by itself, very interesting, but my real goal is something else. I think these techniques form a set of basic building bloc…
Here, I want to present a simple and conservative approach of implementing a weighted majority rule ensemble classifier in scikit-learn that yielded…
In this article, I want to share my experience with a recent data mining project which probably was one of my most favorite hobby projects so far. It’s all…
Last week, I posted some visualizations in context of Happy Rock Song data mining project, and some people were curious about how I created the word clouds…
In this guide we are going to discuss how to install and use the Datumbox Machine Learning framework in your Java projects. Since almost all of the code is written in Java, using it is as simple as including it as dependency in your Java project. Never…