In this capstone, we will predict if the Falcon 9 first stage will land successfully. SpaceX advertises Falcon 9 rocket launches on its website, with a cost of 62 million dollars; other providers cost upward of 165 million dollars each, much of the savings is because SpaceX can reuse the first stage. Therefore, if we can determine if the first stage will land, we can determine the cost of a launch. This information can be used if an alternate company wants to bid against SpaceX for a rocket launch.
- We collect data on the Falcon 9 first-stage landings. You will use a RESTful API and web scraping. You will also convert the data into a dataframe and then perform some data wrangling.
- We perform some EDA using SQL, we also use data visualization to visualize the data and extract meaningful patterns to guide the modeling process.
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We build a dashboard to analyze launch records interactively with Plotly Dash. we then build an interactive map to analyze the launch site proximity with Folium.
- We use machine learning to determine if the first stage of Falcon 9 will land successfully. we will split our data into training data and test data to find the best Hyperparameter for SVM, Classification Trees, and Logistic Regression. Then find the method that performs best using test data.
- we compile all of our activities into one place and deliver our data-driven insights to determine if the first stage of Falcon 9 will land successfully.
MIT