In this project, I have explored data collected by a team of Polish economists studying bankruptcy. The goal is to build a model that can predict whether a company will go bankrupt or not.

• Navigate a file system from the Linux command line
• Extract data that’s been stored in a JSON file.
• Address imbalanced data using resampling techniques
• Expand decision tree model into an entire forest (ensemble model)
• Use a grid search to tune hyperparameters; and create a function that loads data and a pre-trained model, and uses that model to generate a Series of predictions.
• Build a Gradient Boosting Trees ensemble model and evaluate the model by performance metrics to evaluate it

Link to GitHub Repository