Machine learning is the science of teaching computers to reproduce the assigned procedure without being explicitly programmed. It has been widely used not only in engineering (hydroinformatics, bioinformatics, genomics, geosciences and remote sensing, mechatronics) but also in economy, health sciences and even in real estates industry.

This workshop series provides an overall introduction to machine learning specifically with Python programming language which utilizes abundance of scikit-learn package.  Be sure to register for both workshops.

Part 1: Intro to Machine Learning, scikit-learn package and data pre-processing, post-processing using evaluation metrics. Some supervised learning algorithm (regression analysis, distance-based algorithm, tree-based algorithm, Bayes algorithm, support vector machines).  

Part 2: Ensemble approach in ML, Variable Selection & Dimensionality Reduction and Unsupervised Learning. 

Users need to be familiar with basic Python programming and have an m2 account in order to use m2 HPC.