shakiliitju/Credit-Card-Fraud-Detection-Using-Machine-Learning ? reverse-engineered prompt

Build me a Jupyter Notebook project that detects credit card fraud from transaction data and compares a few machine learning models on the same dataset.

I want it to load the Kaggle credit card fraud dataset, clean and prepare the data, then train and evaluate K nearest neighbors, logistic regression, support vector machine, and decision tree models. Please include the usual analysis a student project would need, like checking the class balance, showing a few simple graphs, splitting the data into train and test sets, and reporting the results clearly so I can compare which model works best.

Make the notebook easy to read, with explanations in plain English and enough output to understand what is happening at each step. If you need to look up current docs online for any library details, go ahead. The end result should feel like a complete academic style fraud detection project that I can run and present.