Extract features from a set of given raw data and construct a feature space/feature spaces to develop and train machine learning models for classifying birds: Cardinal, Sparrow, and Crow

Developed classifiers for the distinct categories of datasets and evaluated them by using qualitative measures. Regression-based modeling and Random Forest

Applied Principal Component Analysis (PCA) to the feature spaces created. Then generated new feature spaces using PCA to study the performance changes in confusion matrix