Fraud Detection Using Machine Learning – Full Python Data Science Project (94% Accuracy)

Learn how to build a powerful fraud detection system using machine learning in this full Python data science project! In this step-by-step tutorial, we dive into the techniques that achieved an impressive 94% accuracy in detecting fraudulent transactions. You’ll explore essential machine learning concepts, including data preprocessing, feature engineering, model selection, and evaluation. By the end of this project, you’ll have a strong understanding of how to implement and optimize a fraud detection model in Python using popular libraries like Pandas, Scikit-learn, and Matplotlib. Whether you're a beginner or experienced data scientist, this project will enhance your skills and provide valuable insights into real-world applications of machine learning.

Dataset: https://www.kaggle.com/datasets/amanalisiddiqui/fraud-detection-dataset?resource=download

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00:00 Introduction
00:27 Dataset Card
02:43 Exploratory Data Analysis
23:07 Feature Engineering & Training a ML Model
33:42 Streamlit Web App
43:18 Outro
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