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As of today, we are aware of over 5,600 exoplanets. Detecting these worlds is the initial step; we must also comprehend and characterise their nature by studying their atmospheres. In 2029, ESA Ariel Mission will conduct the first comprehensive study of 1,000 extrasolar planets in our galactic neighbourhood. \n\nSo, the objective is to **analyze astronomical data** and develop machine learning models to solve one of the most formidable challenges in the field, that is, **extracting faint exoplanetary signals** from **simulated observations** of the upcoming ESA Ariel Mission. This project is part of a binary classification challenge which was hosted on Kaggle. Submissions were evaluated using **Gaussian Log Likelihood (GLL)**.\n\n---\n\n## 🔗 References\n\n- 📁 Kaggle Competition: \u003ca href=\"https://www.kaggle.com/competitions/ariel-data-challenge-2024\" target=\"_blank\"\u003eNeurIPS - Ariel Data Challenge 2024\u003c/a\u003e\u003cbr\u003e\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkrishnaura45%2Fastro-pulse","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkrishnaura45%2Fastro-pulse","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkrishnaura45%2Fastro-pulse/lists"}