Ilan Man works in Strategy Operations at Squarespace where he analyzes event-based datasets and builds predictive models in R and Python. He is also a regular speaker at NYC Open Data Meetup. In this talk Ilan will build upon the topics discussed in his earlier presentation (Machine Learning in R), and cover the following:

- Logistic Regression: determining and approximating the cost function
- PCA: eigenvalue decomposition and derivation (basic knowledge of linear algebra assumed)
- Clustering: 3 types of common clustering techniques and examples, pros and cons
- Decision Trees: various implementations, entropy and other tree-features discussed.

Some prior knowledge of these algorithms is helpful, but not assumed.

His talk will be in R, however knowledge of R is not necessary to attend. If you'd like to follow along, having RStudio installed is recommended, as Ilan will be using datasets from the UCI Machine Learning Repository in his talk.