This course will introduce you to some of the most widely used predictive modeling techniques and their core principles. Models such as multiple linear regression, logistic regression, auto-regressive integrated moving average (ARIMA), decision trees, and neural networks are frequently used in solving predictive analytics problems.

Learning Objectives - In this module you will learn about the Recommendation platforms and implement a Recommender using MapReduce. Topics - User based recommendation, User Neighbourhood, Item based Recommendation, Implementing a Recommender using MapReduce, Platforms: Similarity Measures, Manhattan Distance, Euclidean Distance, Cosine Similarity, Pearson's Correlation Similarity, Loglikihood Similarity, Tanimoto, Evaluating Recommendation Engines (Online and Offline), Recommendors in Production.