When building machine learning and artificial intelligence models you’ll often run into situations where a model is not working as well as you would like. Maybe the error rate is too high or the model works fine on the training data, but fails when you apply real world data. What should you do to improve […]


This post will discuss how adding regularization to your machine learning algorithms can improve the accuracy of your algorithm. We will walk through an example of regularization in linear regression, and see how different amounts of regularization impact the accuracy.¬† Under-fitting and Over-fitting When we designing machine learning algorithms we risk over-fitting and under-fitting our […]


To be able to solve a problem using machine learning¬†or AI it is important we know how to categorize the problem. Categorizing the problem helps us understand which tools we have available to help us solve problem. This article will help you understand the different types of machine learning problems, and provide examples of algorithms […]