CLI using click (commands: predict, train, evaluate) with settings set via flags or environment variables
GUI using gradio (tabs: predict, train, evaluate, compare, settings)
For the sklearn model, add more classifiers
Use random search for hyperparameter tuning and grid search for fine-tuning
Finish the text pre-processing transformer
For vectorization, use custom stopwords
Write own tokenizer/vectorizer
Add more datasets
Add more models (e.g. BERT)
Write tests
Use xgboost?
Deploy to huggingface?