🚨 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
🔔 Don’t forget to like, share, and subscribe for more practical AI & ML content!
#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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