In this data science project in R, we are going to talk about subjective segmentation which is a clustering technique to find out product bundles in sales data.

In this deep learning project, we will predict customer churn using Artificial Neural Networks and learn how to model an ANN in R with the keras deep learning package.

This is in continuation of the previous Hive project "Tough engineering choices with large datasets in Hive Part - 1", where we will work on processing big data sets using Hive.

In this machine learning and IoT project, we are going to test out the experimental data using various predictive models and train the models and break the energy usage.

In this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.

In this spark project, we will continue building the data warehouse from the previous project Yelp Data Processing Using Spark And Hive Part 1 and will do further data processing to develop diverse data products.

In this big data project, we will continue from a previous hive project "Data engineering on Yelp Datasets using Hadoop tools" and do the entire data processing using spark.