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a-predictive-analytics-model-to-classify-bankruptcy-for-a-firm

The objective of the project was to develop a predictive model that combines various econometric measures to foresee a financial condition (Bankruptcy or not) of a firm based on a financial balance sheet data set available on Kaggle. This was done as part of the Data Mining course at the Krannert Business Analytics Program, Purdue University - Team: Zaid Ahmed, Mohinder Goyal and Maharshi Dutta

analytical-sql-examples

NO LONGER MAINTAINED. Code samples for Oracle's analytical SQL features

covid19italy

Italy covid19 data

data

Data and code behind the articles and graphics at FiveThirtyEight

model_search

portfolio-optimization-and-predicting-stock-price

The Objective was to built a predictive model with an interactive UI to help optimize Portfolio selection and also predict the stock price after 3 months. The Krannert Business analytics team for this was: Arun Ramakrishnan, Abhinav Chanda, Seshu Tai, Sagar Kurada and Maharshi Dutta

retail-demand-forecasting-model-using-factorization-machines

It is challenging to build useful forecasts for sparse demand products. If the forecast is lower than the actual demand, it can lead to poor assortment and replenishment decisions, and customers will not be able to get the products they want when they need them. If the forecast is higher than the actual demand, the unsold products will occupy inventory shelves, and if the products are perishable, they will have to be liquidated at low costs to prevent spoilage. The overall objective of the model is to use the retail data which provides us with historic sales across various countries and products for a firm. We use this information given, and make use of FM’ s to predict the sparse demand with missing transactions. The above step then enhances the overall demand forecast achieved with LSTM analysis. As part of the this project we answered the following questions: How well does matrix factorization perform at predicting intermittent demand How does matrix factorization approach improve the overall time-series forecasting

timeseries-aiengineering

This is a repo for all the time series related notebook for AIENgineering

wom-restaurant-recommendation

This project is for MGMT 590-Using R for Analytics at Krannert School of Management, developed by Team Revengers: Arun Ramakrishnan, Juily Vasandani, Maharshi Dutta, Samir Husain, Yizhu Liao. This is a restaurant recommendation system which finds closest restaurant based on user reviews.