This is a demonstration of using Python to build a simple ML model. Tasks are the following:
- Load data from a FASTA file
- Extract features from each nucleotide sequence
- Visualize data using Principal Component Analysis and Seaborn
- Train a Gradient Boosting classification model
- Evaluate performance on a test set and inspect a confusion matrix