Description
- Date: December 31, 2023
- Categories: Deep LearningEDAMachine LearningPython
Overview
This project applies machine learning to detect credit card fraud using a Kaggle dataset. It includes data preprocessing, exploratory analysis, and model training and evaluation.
Technologies
- Python, Pandas, NumPy
- Matplotlib, Seaborn
- Scikit-learn, XGBoost, PyTorch
Objectives
- Perform EDA on the credit card transaction dataset.
- Develop and assess Logistic Regression, XGBoost, and a custom MLP model using PyTorch.
- Compare model performances using metrics like accuracy and F1 score.
Learning Outcomes
- Enhanced data preprocessing and analysis skills.
- Experience in implementing various machine learning models.
- Insights into model evaluation and comparison in fraud detection.