This project leverages the StreamLit library to create a web-based dashboard that analyzes Kaggle's Titanic passenger survival data set. Key aspects of this dashboard include:
- Machine learning: Uses the Sklearn library to create a decision tree classifier, which the user is able to customize and test.
- Data visualization: Using the Plotly library, a visualization of the decision tree classifier is created. These visualizations are tailored to user input, as they can change the max depth of the model.
- Data management: An initially messy dataset is filtered, cleaned, sorted, and analyzed as a pandas dataframe. Demonstration using Kaggle's Titanic dataset.
