This project focuses on predicting potential collisions between asteroids and Earth. It achieves this by leveraging machine learning and statistical techniques to build predictive models.

The dataset utilized in this project contains valuable information about potential asteroid impacts with Earth and various characteristics of known near-Earth asteroids. Access the dataset here.

• Analyze the structure of the dataset to identify pertinent attributes for prediction.

• Clean and preprocess the dataset to handle missing values, outliers, and ensure data quality.

• Utilize machine learning and statistical methods to construct predictive models for estimating the likelihood of impact.

• Fine-tune model hyperparameters to enhance performance and prevent overfitting or underfitting.

• Validate model performance using appropriate techniques and test on unseen data to ensure robustness.

• Create an engaging presentation summarizing the problem statement, dataset specifics, the chosen approach/methodology, and the obtained results.