Build a Fraud Detection Model from Scratch | Real-World Project with EDA

🚨 Credit Card Fraud Detection Using Machine Learning – Full Project Tutorial 🚨

In this in-depth video, we take you through a complete end-to-end machine learning project on credit card fraud detection using a real-world dataset. From exploratory data analysis (EDA) to model building, everything is covered in one power-packed session!

🎯 What You’ll Learn in This Video:

Understanding the fraud dataset

Performing data cleaning & preprocessing

Handling class imbalance with techniques like SMOTE

Visualizing fraud patterns with insightful plots

Building and evaluating ML models (Logistic Regression, Random Forest, etc.)

Model performance metrics like precision, recall, F1-score, and confusion matrix

📊 Whether you’re a data science beginner, a student building your portfolio, or someone preparing for ML job interviews, this project will give you practical experience on a real business problem.

🔧 Tools Used:

Python

Pandas, NumPy

Matplotlib, Seaborn

Scikit-learn

Imbalanced-learn (SMOTE)

💼 Perfect For:

Final year college students

Job seekers in data science

Anyone learning machine learning through real projects

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#CreditCardFraudDetection #MachineLearningProject #DataScience #EDA #ImbalancedDataset #PythonML #AIProject

Visit Us : https://saidatascience.com
Download the Notebook : https://colab.research.google.com/drive/19cJoFPDlCnt9F7ikW-M4E3OQHf6ihj-X?usp=sharing

Dataset Link : https://drive.google.com/file/d/1nqcWbrr04bDfgmSbwyLM07josvPrlrWJ/view?usp=sharing

Join Whatsapp group for Queries : https://chat.whatsapp.com/LJEJ0DB8YiKIerBtHeERAB

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