SpaceX-Falcon-9-first-stage-Landing-Prediction
Predicting successful landings of SpaceX Falcon 9's first stage using machine learning.
Created on 28th January 2025
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SpaceX-Falcon-9-first-stage-Landing-Prediction
Predicting successful landings of SpaceX Falcon 9's first stage using machine learning.
The problem SpaceX-Falcon-9-first-stage-Landing-Prediction solves
This project uses machine learning to predict whether SpaceX Falcon 9's first stage will successfully land after launch. By analyzing factors such as fuel levels, velocity, and trajectory, the model helps to improve the success rate of landings, making space exploration more cost-efficient and reliable. This technology could be used for mission planning, providing better insights to engineers and mission control teams, ensuring better safety, and reducing the costs of space missions by maximizing the reuse of rocket stages.
Challenges I ran into
One of the major challenges was dealing with the imbalanced dataset, where the number of successful landings was much smaller than unsuccessful ones. To overcome this, I implemented techniques like oversampling the minority class (successful landings) and fine-tuning my model to handle class imbalance. I also faced challenges with feature selection, where I had to determine the most relevant features for accurate prediction. This was solved by using feature engineering and recursive feature elimination.