Stochastic processes have many applications, including in finance and physics. It is an interesting model to represent many phenomena. Unfortunately the theory behind it is very difficult, making it accessible to a few 'elite' data scientists, and not popular in business contexts.

One of the most simple examples is a random walk, and indeed easy to understand with no mathematical background. However, time-continuous stochastic processes are always defined and studied using…

Here is our new selection of articles and resources recently posted:

• Comparison of Deepnet & Neuralnet 
• Google Tutorial on Machine Learning …

Summary:  Here are our 6 predictions for data science, machine learning, and AI for 2018.  Some are fast track and potentially disruptive, some take the hype off over blown claims and set realistic expectations for the coming year.

It’s that time of year again when we do a look back in order to offer a look forward.  What trends will speed up, what things will actually happen, and what things won’t in the coming year for data science, machine…

Here is our selection of featured articles recently posted:

• Enterprise AI: Learning from the evolution of Robotic Process Autom...
• Book: Introduction to Statistics …

Summary:  As a profession we do a pretty poor job of agreeing on good naming conventions for really important parts of our professional lives.  “Machine Learning” is just the most recent case in point.  It’s had a perfectly good definition for a very long time, but now the deep learning folks are trying to hijack the term.  Come on folks.  Let’s make up our minds.

As a profession we do a pretty poor job of agreeing on good naming conventions for…

Here is our selection of featured articles and resources posted recently:

• Free eBook: Applied Data Science (Columbia University) 
• Some Deep Learning with Python, TensorFlow and Keras …