Offices iha website nee la’ós kantor fisiku, maibé unidade akademiku ne’ebé ajuda estudante sira aprende teori Supervised Learning ho maneira estruturadu no sistemátiku.
Parte ida nee esplika teori dasar Supervised Learning, hanesan definisaun, konsep input no output, label, no diferensa klasifikasaun ho regresaun.
Iha ne’e ita aprende kona ba algoritmu Supervised Learning hanesan Linear Regression, Logistic Regression, Decision Tree, KNN, no SVM.
Office ida nee esplika saida mak dataset, diferensa data training ho data testing, no oinsa dadus ho label uza iha Supervised Learning.
Parte ida nee esplika proses training model, tahapan Supervised Learning, no oinsa sistema aprende husi dadus ne’ebé iha label.
Iha ne’e ita aprende oinsa avalia model, hanesan accuracy, precision, recall, no confusion matrix hodi haree rezultadu model.
Office ida nee fo ezemplu kazu real, hanesan klasifikasaun spam email, predisaun nilai estudante, no aplikasaun Supervised Learning iha moris loron-loron.