cost-benefit-analysis
There are 23 repositories under cost-benefit-analysis topic.
ztqsteve/Uber-Rider-Churn-Analysis
Uber is interested in predicting rider retention. To help explore this question, they have provided a sample dataset of a cohort of users.
Vishal-V/RainRoof
Watershed, Canny and Mask R-CNN based rooftop volume computation from scaled satellite images. This is similar to Google's SunRoof project.
CIAT/cleaned
Inclusive and Comprehensive Livestock Environmental Assessment for Improved Nutrition, a Secured Environment, and Sustainable Development along Livestock Value Chains
7er/elm-nka
nka verktøy for uu-tiltak i kollektivtrafikken
liyouzhang/Churn_Prediction
Predict churning or not from the real-world data of a ridesharing app
AmandaFernandes0701/Projeto-DTI
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.
liyouzhang/Fraud_Detection
An event website is curious to know how can we use Machine Learning to predict an event posted live is a fraud or not.
myklob/ideastockexchange
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.
mcarpanelli/Churn-Prediction-Rideshare
Data Science Case Study
DAboaba/cost_benefit
This repository contains code to run a cost-benefit analysis (at the level of individual incidents) for a violence intervention program.
deepakrameshgowda/CREDIT-CARD-FRAUD-DETECTION
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.
divyank97/Churn_Pred_Cost_Benefit_Analysis
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.
MadisonCostanza/Crawford-Development-Co.-Project-Risk-Analysis
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.
Mayowa1012/Newspaper-Digital-Subscribers
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 therefore interested in developing strategies to manage subscriber churn rate. A proposed initiative is to offer 25% discount to inactive subscribers. In a bid to achieve this, the company is looking to develop a model that can predict possible customer/subscriber churn, in order to minimize financial loss and cost incurred in gaining new market entrance/confidence. Upon achievement of this goal, the company will be able to minimize subscriber churn and achieve overall business success.
richengo/WNV-Predictions
Kaggle Competition: Predictions of West Nile Virus outbreaks in the City of Chicago.
SowmyaKothari/Credit-Card-Fraud-Detection
Machine learning-based fraud detection system capable of identifying and preventing fraudulent transactions in real-time for Finex, a financial service provider based in Florida.
syimii/Decision-Making-In-Purchasing-House-New-House-Or-Subsale-Using-CBA
Decision of a purchase depends on affordability of the house, its neighbourhood, location from important venues such as office, school, and groceries store.
tiaplagata/dsc-phase-3-project
My third Data Science Project at Flatiron School! Exploratory Data Analysis and Classification Modeling-- classifying customer churn in the telecommunications industry using a Gradient Boosted Classifier.
yk0766/Loan-Default-Prediction-R-programming
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.
hendersontrent/qldyjcost
Simple R package for costs and calculations of youth offending in Queensland, Australia
twliam/West-Nile-Virus-Prediction
GA project 04