Intermediate R workshop: Logistic Regression, PCA and clustering

NYC Open Data
NYC Open Data
Public group
Location image of event venue

Details

Social Media:

Twitter: @Vivian__Zhang (https://twitter.com/vivian__zhang) @SupStat (https://twitter.com/supstat) @NycDataSci (https://twitter.com/NycDataSci)

Learn with our NYC Data Science Program (http://www.nycdatascience.com/) (We offered corporate and individual training for more than 40 firms in NYC alone). We offer 12 week immersive program, weekend and weekday night Data Science training.

Speaker:

Ilan Man, adjunct instructor of NYC Data Science Academy will present Machine Learning in R, and cover the following:

Ilan Man works in Strategy Operations at Squarespace where he analyzes event-based datasets and builds predictive models in R and Python.

Topic:

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.