A hospital is evaluating the efficiency of Insulin based treatment for diabetes patients. The Objective is to recommend whether solo insulin or conjunction of other drugs/ treatment is more effective at treating diabetes based on analyzing the patient's medical history.

A store has a loyalty program and wants to provide offers on products during the non-sale period on certain categories of interest. Based on the Black day sales data, recommend the top 100 products it must prioritize for loyalty rewards to customers.

A house value is simply more than location and square footage. Like the features that make up a person, an educated party would want to know all aspects that give a house its value. For example, you want to sell a house and you don’t know the price which you can take — it can’t be too low or too high. To find the house price you usually try to find similar properties in your neighbourhood and based on gathered data you will try to assess your house price.

To develop the credit scorecard using a regression model, where the past data of the existing loans & default cases can be used to enable the investor to predict the probability of default for a potential loan to be given to the new loan applications from the borrowers and based on the risk categorization / risk bucketing suggest suitable interest rates to be charged to hedge the risk involved.

The objective is to analyse P2P Lending loan transaction data from one of major US market players for over a decade and build a model for identification and recommendation of borrowers/loan for an investor. Overall, you will have the effort in these themes 1. Predict the interest rate of potential lenders 2. Predict the probability of default for a potential loan.

Under the project study, you will try to utilize the dataset containing information about a set of engineering graduates and their employment outcomes to analyse the following few use cases – 1. Given a new student profile, predict his/her annual salary from historic data. 2. Predict what factors in the labor market determine one’s salary. Is it just one’s skills or are there other factors that influence the return in the labor market.

There has been year on year analysis on money spent by franchises on the teams and their performance over IPL. The objective of this capstone project is to determine the relationship between money involved in a match (i.e. money spent to buy the playing 11 players) and chances of winning.

People often spend a lot of time browsing through online shopping websites, but the conversion rate into purchases is low. Determine the likelihood of purchase based on the given features in the dataset. The dataset consists of feature vectors belonging to 12,330 online sessions. The purpose of this project is to identify user behaviour patterns to effectively understand features that influence the sales.