Machine Learning with R

About Us

We work on open-source data projects and do education,consulting, and training in machine learning and statistics. From time to time, we release our open data work through free and open-source materials(projects) which we share through our data lab. These examples were originally blog posts created in June 2014 which we released as an open data case study.

About this project

This machine learning cookbook is a compilation of a series of posts on applied statistical methods and predictive machine learning on home mortgage disclosure data from Vermont for 2012. The aim is to explore various models and gain insights from the data.

The Home Mortgage Disclosure Act(HMDA) has been collecting data on loan applications and originations since 1975. Recently, this data has been made available by the Consumer Financial Protection Bureau. This database provides detailed information on loan data that is required by HMDA. In this analysis, statistical methods will be used to answer research questions and explore hypotheses.

There are many how-to and theory books on machine learning available. The aim here is to introduce practical applications of algorithms by exploring selected topics. This cookbook assumes basic familiarity with R, statistics, and machine learning. The intended audience is familiar with statistical modeling techniques and machine learning algorithms.