Train a Two-Class Boosted Decision Tree Model on preprocessed data to predict an individual's income in the US.
The estimator used in this project is a Two-Class Boosted Decision Tree classifier. The ML pipeline includes data-preprocessing (Data Cleaning, Accounting for Class Imbalance) and Hyperparameter Tuning. Some of the features used to train the model are age, education, occupation, etc. Deployed the trained model as an Azure Machine Learning web service to input new data to the web service API and receive the resulting predictions.