Each project comes with 2-5 hours of micro-videos explaining the solution.
Get access to 50+ solved projects with iPython notebooks and datasets.
Add project experience to your Linkedin/Github profiles.
The weekly sales transaction dataset consists of weekly purchased quantities of 800 products over 52 weeks. Normalised values are provided too. The objective of this data science project in R is to find out product bundles that can be put together on sale. Typically Market Basket Analysis was used to identify such bundles, here we are going to compare the relative importance of time series clustering in identifying product bundles.
Given a partial trajectory of a taxi, you will be asked to predict its final destination using the taxi trajectory dataset.
Machine Learning Project in R- Predict the customer churn of telecom sector and find out the key drivers that lead to churn. Learn how the logistic regression model using R can be used to identify the customer churn in telecom dataset.
In this project, we are going to talk about H2O and functionality in terms of building Machine Learning models.