ML AI DL
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Updated
Mar 29, 2020 - Jupyter Notebook
ML AI DL
Credit card fraud detection
implementation of some ml algorithms
Data Science Project
Official Flutter package for Greip API
In this project, the ML algorithm should detect the fraud clicks, taking the click time, IP address, app_id, etc into account. The provided data is very unbalanced with less than 1% fraud clicks.
Worked on detecting illicit transactions in the Ethereum Transactions dataset by increasing our dataset size, and with little tolerance to missing fraudulent transactions.
Sirius.AI Research Programme (Spring 2024), DataBarrels Team. Blockchain AML.
In this project a model was build to identify and predict fraudulent credit card transactions.
This repository contains some of my machine learning notebooks I created on Kaggle
Fraud risk is everywhere, but for companies that advertise online, click fraud can happen at an overwhelming volume, resulting in misleading click data and wasted money.
A collection of machine learning mini-projects.
This repo has a notebook that I worked on for making a fraud detection model. The dataset was Highly imbalanced, so i used random undersampling to balance the data.
Anonymized credit card transactions labeled as fraudulent or genuine
Detect payment transaction fraud using feature engineering and traditional and deep Machine Learning models.
Solution of the issue of classifying banking transactions (detecting fraudulent transactions)
Predicting the genuity of a transaction based on anonymized credit card transaction data.
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