This repository contains my final project made for 'IBM Data Science Professional Certificate' course. The project focuses on predicting the successful landing of the Falcon 9 first stage.
The objective of this project is to predict whether the Falcon 9 first stage will land successfully. SpaceX advertises Falcon 9 rocket launches on its website, with a cost of $62 million. Compared to other providers, which cost upwards of $165 million each, much of the savings is attributed to SpaceX's ability to reuse the first stage. Therefore, accurately determining the first stage's landing success can help estimate the cost of a launch. This information is valuable for alternate companies considering bidding against SpaceX for a rocket launch contract.
- Notebooks: Contains the code and analysis for predicting Falcon 9 first stage landings.
- Data: Data files used in the analysis.
- README.md: Overview of the project and instructions.
- Python programming language
- Data analysis and visualization libraries (NumPy, Pandas, Matplotlib, Seaborn)
- Machine learning algorithms (Logistic Regression, Random Forest, etc.)
To run the Jupyter Notebook containing the project code, make sure you have Jupyter Notebook installed. Then, open the notebook in your preferred environment and execute the code cells sequentially.
This project is licensed under the GNU General Public License.