Machine Learning is the general study of programs that learn from data. Machine Learning algorithms can be used to write software that we don't know how to write directly (e.g., spam filters, image classification, handwriting recognition, etc.).
This is a huge and broad topic. My goal is to give an introduction. Regardless of what type of software you write, chances are there are ways to employ some type of machine learning or data analysis algorithm to do something cool.
Introduce some basic machine learning concepts (e.g., data representation, feature spaces, etc.)
Describe and discuss different machine learning problems (e.g., regression, classification, clustering), their applications, and some of the algorithms used to solve them.
This will mostly be a conceptual talk. All of the topics covered will be programming language agnostic.
About Matt Nedrich:
Matt is a software engineer with an interest in a variety of computer science and mathematics topics. He has a M.S. in Computer Science and Engineering from The Ohio State University. For the past three years he has worked on CPU and SOC validation/characterization at Intel. He recently moved to Ann Arbor in 2013.