Evaluation of post-lockdown policies using social contacts and risk of professional exposure.
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Updated
May 3, 2020
Evaluation of post-lockdown policies using social contacts and risk of professional exposure.
I built and evaluated several machine-learning models to predict credit risk using free data from LendingClub. I employed different techniques for training and evaluating models with imbalanced classes and used the imbalanced-learn and Scikit-learn libraries to build and evaluate models.
To identify customers who are more likely to default loan repayment
Biblioteca para mercado financeiro
Vigilante Vixen has learned that there were many security vulnerabilities from their technical, behavioral, law, and human resources aspects. Despite us not being directly involved in offshore financial services or the legal profession, technology roles have a considerable amount of opportunity to review this case and implement security regulations
Cyberus is a tool to check the generic and sentimental legitimacy of the message, and it gives an approximate idea of the risk, based on the dataset, on which it has trained, and some machine learning models for predicting the risk quantitatively.
(Machine Learning/Data Science) Insurance Risk Assessment. Predicting insurance policy claims. Using machine learning and customer data to predict whether insurance policy holders will initiate an auto insurance claim within the next year.
A Whale off the Port(folio)
Develop a model for predicting fraudulent transactions for a financial company and use insights from the model to develop an actionable plan.
In this project, we'll analyse data from italian stock market for bank stocks.
In this project, we aim to optimize the performance of retail chain stores by establishing control stores based on their performance compared to selected trial stores. By leveraging data analytics and strategic insights, we seek to enhance sales revenue and drive growth within the retail chain.
Anonymized report from one of Safety AI's consulting projects
Project source code and data for ML-enhanced risk analysis framework for combustion instability prediction
This project applies supervised machine learning models to predict credit risk, and compare algorithm effectiveness in an unbalanced classification problem
This is an in-depth analysis tool for equity fund managers focusing on large-cap shares.
This repository contains a Monte Carlo simulation and risk analysis model developed to analyze customer spending and daily revenue fluctuations for a grocery store across four product categories: fresh baked goods, meat and dairy, produce, and frozen food.
Risk Management for Information Security
I use logistic regression and random forests to build a model that can predict whether or not a borrower will pay off their loan
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