This data science project entails collecting SpaceX data through webscraping and APIs, performing exploratory data analysis and data wrangling and finally building machine learning models to predict if a Falcon 9 first stage landing will be a success which can then lead onto determining cost of launches and thus, enabling companies to bid against SpaceX regarding rocket launches.
Results:
A decision tree model is selected at the end as it generates an accuracy of 94% on the test set compared to other models such as KNNs, SVMs and Logistic Regression which only up to 83.33%