Machine Learning using Python

Instructor

• Instructor: Carl Ehrett

• Office: 2105 Barre Hall, Clemson University

• Email: cehrett@clemson.edu

Workshop Description

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 the Python programming language. Types of machine learning 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.