This file covers some basic solutions for the Cascade Cup 22 Hackathon. The problem was to predict whether a delivery person will cancel an order allotted to them. The ipynb file includes preprocessing of the data, testing various base algorithms, applying various balancing techniques on the data, and creating a prediction file for the hackathon.
This is a classification problem from a Kaggle Dataset. The problem is to predict whether an employee will leave/be laid off within the next year from a company. It includes variables like Employee Satsifaction, Performance, etc.
This is a multi-class classification problem, where we try to predict the Obesity Level of a person using various medical metrics as well as some lifestyle indicators.
This project aims to predict whether an employee will leave the company or be fired within the next time duration, based on various provided factors.
The aim of this project was to build a Decision Tree Model that predicts the Interest Rate category under which an application should fall. The dataset included variables like Loan Amount, Annual Income, Purpose of Loan, etc. There were three categories of Interest Rate - 1, 2 and 3.