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classification-algorithms

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This project focuses on the detection of credit card fraud using various data science and machine learning techniques. The dataset includes a record of credit card transactions over a specific period, with the goal of accurately identifying fraudulent activities. 🚀✨

  • Updated Mar 30, 2024
  • Jupyter Notebook

Focused on advancing credit card fraud detection, this project employs machine learning algorithms, including neural networks and decision trees, to enhance fraud prevention in the banking sector. It serves as the final project for a Data Science course at the University of Ottawa in 2023.

  • Updated Jan 10, 2024
  • Jupyter Notebook

This repository contains all the machine learning algorithms studied in discipline "Engenharia Médica Aplicada" of Biomedical Engineering course at UNIFESP in the second semester of 2018. All the algorithms are written in both MatLab and Python Languages.

  • Updated Mar 3, 2020
  • MATLAB

Built a classifier to predict whether a loan case will be paid off or not. Used classification algorithms (k-Nearest Neighbour, Decision Tree, Support Vector Machine, Logistic Regression). Each result is reported with the accuracy of each classifier (Jaccard index, F1-score, LogLoass)

  • Updated Nov 3, 2020
  • Jupyter Notebook

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