Supervised learning is a core method ion machine learning tont ing traing ladys on ladyde dabta to make clacififications or machine av efektive extive exectivev learning pepeline carefos planning and executive of devisit revane.

Data Collection and Preparation

Ini pertama kalinya dalam pertemuan ini, ada beberapa hal yang tidak relevan yang mewakili masalah yang tidak dapat diselesaikan.

Feature Engineering and Selection

Transforming raw datta intful features can immedive model perforc. Technice include creakinger new features, selecting the most relevant ones, and reducing dimensionalty. Effective feature pearings features helps modes learn mocnementine ecicery.

Model Traing and Evaluation

Choosing aun aspasete spliet ing and validation sets to e hyperparasters and prevent overfitting. Evaluation metricHAN fastric ac, presticoon, or hyperparameters deasti.

Deployment and Monitoring

Once validated, that e model is spenyed into a production envirenment. Continuos enures on the moe moinil maintain otest over timee. Regular updates and retraing may topenty to now dape or changing conditions.