<ul><li>The project aimed to disrupt the insurance industry by integrating machine learning models to enhance the accuracy of insurance predictions.</li><li>Using Python, a machine learning model was built to predict insurance costs based on user demographics and health information.</li><li>Challenges included dealing with incomplete and imbalanced datasets, which were addressed through data imputation techniques and balancing methods.</li><li>The model achieved impressive accuracy, surpassing traditional statistical approaches and opening possibilities for further refinement.</li></ul>

Insurance Prediction Machine Learning

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