Uber is interested in predicting rider retention. To help explore this question, they have provided a sample dataset of a cohort of users.

Watershed, Canny and Mask R-CNN based rooftop volume computation from scaled satellite images. This is similar to Google's SunRoof project.

Comprehensive Livestock Environmental Assessment for Improved Nutrition, a Secured Environment, and Sustainable Development along Livestock and Fish Value Chains (CLEANED)

nka verktøy for uu-tiltak i kollektivtrafikken

Predict churning or not from the real-world data of a ridesharing app

An event website is curious to know how can we use Machine Learning to predict an event posted live is a fraud or not.

In summary, the project performs the following action: based on the data provided by the user, it checks which pet shop offers the best cost-benefit ratio for the client.

Empowering Rational Discourse and Decision-Making: The Idea Stock Exchange is a groundbreaking platform designed to revolutionize how we engage in political and societal debates. At its core, this project harnesses the power of collective intelligence, utilizing a structured framework for automated conflict resolution and cost-benefit analysis.

Data Science Case Study

This repository contains code to run a cost-benefit analysis (at the level of individual incidents) for a violence intervention program.

Decision of a purchase depends on affordability of the house, its neighbourhood, location from important venues such as office, school, and groceries store.

Kaggle Competition: Predictions of West Nile Virus outbreaks in the City of Chicago.

This is an analytical project I completed during an Enterprise Risk Analytics course for my Master's Program at Boston University. The project explores two real estate development options from the perspectives of a development company and regional bank.

Building predictive models to detect and prevent the fraudulent transactions happening on cerdit cards and debit cards. Implementation of 2nd factor authentication for safe and secure transactions.

GA project 04

Simple R package for costs and calculations of youth offending in Queensland, Australia

In this project, we have analyzed, explored and processed the data, developed and evaluated various classification and regression models to provide strategies for high returns with low risk for investors.

This project covers a critical analysis of existing subscribers in a daily newspaper company. The dataset adopted for use in this report, comprises of personal information of the company’s digital subscribers. The newspaper company is perceived to be a market leader but has been faced with the challenge of customer retention. The company is ther…