<ul><li>The project focuses on predicting the medal classification of Kaggle datasets using EDA and machine learning techniques.</li><li>EDA and feature engineering were performed to analyze the dataset and improve its quality for modeling.</li><li>Pre-processing techniques such as encoding categorical features and manual feature selection were applied.</li><li>The Random Forest Classifier algorithm was chosen and evaluated based on performance metrics, demonstrating good accuracy in predicting medal categories.</li></ul>

Mastering Kaggle Medal Prediction with EDA and Machine Learning

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