Machine learning in Python (scikit-learn)

Machine learning is the science of teaching computers to reproduce the assigned procedure without being explicitly programmed. It has been used in many practical applications such as self-driving cars, speech recognition, email spam classification. 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 provides an overall introduction to machine learning specifically with Python programming language which utilizes abundance of scikit-learn package. Such topics include:

1. Supervised learning (regression analysis, distance-based algorithm, regularization algorithm, tree-based algorithm, Bayes algorithm, support vector machines, artificial neural networks).
2. Unsupervised learning (clustering, dimensionality reduction).

The course will also draw from numerous case studies and applications that can be applied in different engineering programs.