This problem is fairly simple to describe… given a bunch of variables that describe the various aspects of a house along with a sales price, is it possible to come up with a mathematical model that can be used to predict future prices based on different values of the same variables? It is based housing sales data …

This is originally a Kaggle problem where the task is: to build a predictive model that answers the question: “what sorts of people were more likely to survive?” using passenger data (ie name, age, gender, socio-economic class, etc). The data is broken into train and test sets in a ratio of approximately 68 to 32 …