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pkl-model

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Home Loan Approval Prediction System uses machine learning to predict loan approval outcomes, helping financial institutions streamline decisions. It preprocesses data, handles missing values, encodes features, and uses a Random Forest Classifier for feature selection, optimizing the model for accuracy and efficiency.

  • Updated Dec 29, 2024
  • Jupyter Notebook

This repository contains a machine learning model built to detect fake news articles. The project leverages natural language processing techniques and a supervised learning approach to classify news articles as either real or fake based on their content.

  • Updated Jul 21, 2024
  • Jupyter Notebook

This project aims to detect fraudulent credit card transactions using a machine learning model. The application is built using Flask for the backend and a simple HTML form for the frontend. The model predicts fraud based on the Time and Amount features of the transaction.

  • Updated Jul 21, 2024
  • CSS

Problem Statement: Financial institutions face significant challenges in detecting fraudulent activities due to the large volume of transactions and the sophistication of modern fraud techniques. The problem is to design AI models that can accurately detect fraudulent transactions in real-time while minimizing false positives.

  • Updated Sep 9, 2024
  • Jupyter Notebook

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