A robust Machine Learning–based system designed to predict crime rates across 38 districts of Bihar, leveraging a high-performance Random Forest model (~90% accuracy) and deployed via a Flask web application for real-time insights.
data-science machine-learning random-forest scikit-learn data-visualization crime-analysis crime-prediction crime-data-analysis machine-projects crime-rate-prediction-systems-ml crime-rate-prediction-systems crime-rate-prediction iit-patna-project bihar-crime-analysis crime-rate-prediction-project-using-python crime-rate-project crime-prediction-machine-learning-projec crime-prediction-software crime-prediction-algorithm satywan-prajapati
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Updated
May 19, 2026 - Jupyter Notebook