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.

Inclusive and Comprehensive Livestock Environmental Assessment for Improved Nutrition, a Secured Environment, and Sustainable Development along Livestock Value Chains

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

Software-based rationalia. A structured "Wikipedia for arguments" leveraging collective intelligence to automate enlightenment, conflict resolution, and cost-benefit analysis. This platform revolutionizes political and societal debates through logical ranking, pro/con organization, and rigorous, systemic evaluation frameworks and sustainable logic.

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.

nka verktøy for uu-tiltak i kollektivtrafikken

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

Data Science Case Study

This repository contains an advanced Excel-VBA driven financial analysis tool to evaluate **annealing line investment** improving **narrow-width coil processing** in a steel manufacturing facility

A Python-based DSM Program Calculator compliant with the 2022 IESO Cost Effectiveness Guide (TRC & PAC Tests).

ML-based system to detect fraudulent credit card transactions with cost-benefit analysis.

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.

Methods for estimating sources of BCR change via decomposition into change in benefits and change in costs.

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

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…

This project consists of Churn Prediction using Gradient Boosting algorithm and then formulating a critital analysis report from a business analyst perspective containing the cost benefit analysis for the company to issue incentives based on the prediction.

Binary classification of personal loan acceptance using 8 ML models (RF, GBM, SVM, NN, LDA, Elastic Net) with cost-optimised threshold tuning. MSc ASML summative — Durham University.