Kevin McCarthy will present a gentle introduction to Machine Learning*.
Have you ever wished your computer could do more than what you tell it
to do explicitly? Maybe you want to write a recommendation engine
like the one Amazon and Netflix use to recommend similar products, or
maybe you just want to build Skynet. The goal of this talk is to
give a broad but shallow overview of machine learning techniques and
applications. Topics covered will (probably) include:
- What is machine learning?
- Supervised vs unsupervised machine learning
- Linear Regression
- Partitioning your data into training, test, and cross-validation sets
- Bias/variance tradeoff
- Logistic Regression
- Brief overview of more advanced algorithms such as neural networks
and support vector machines
- Advanced applications such as digit recognition and collaborative filtering
Should be fun!