Monthly Archives: August 2016

Two Ways to Perform Linear Regression in Python with Numpy and Scikit-Learn

Greetings, This is a short post to share two ways (there are many more) to perform pain-free linear regression in python. I will use numpy.poly1d and sklearn.linearmodel. Using numpy.polyfit we can fit any data to a specified degree polynomial by … Continue reading

Posted in Machine Learning, Python Programming | Tagged ,

K-Means Clustering and How it Relates to the Gaussian Mixture Model

Greetings, I would like to write a post on the Gaussian Mixture models. The post would be a tutorial with a, hopefully, intuitive explanation of when and how to use Gaussian Mixture (GM) models. However, before I begin with GM, … Continue reading

Posted in Home, Machine Learning, Python Programming | Tagged ,

Learning Predictive Rules on the Poker Hand Data Set

Hello again, In my last post I have shared a rather simple python code to build a decision tree classifier to recognize a hand in a poker game. The simplicity of my solution stemmed from the fact that I added … Continue reading

Posted in Home, Machine Learning, Python Programming | Tagged ,

Learning Binary Decision Trees from the Poker Hand Data Set

Greetings, my blog readers! What a year this has been so far! I am finally finding some time and energy to write new posts on my blog. I am really looking forward to blogging more about machine learning and data … Continue reading

Posted in Home, Machine Learning, Python Programming | Tagged ,