Akademik Dersler - İçerik

0 : Does not support 1 : Low-level support 2 : Mid-level support 3 : Top level support

Learning Outcomes	1	2	3	4	5	6	7	8	9	10	11	12
Can define a machine learning problem and prepare the data for training using Scikit-learn (train/test split).	3	3	3	3	3	3	3	3	3	3	3	3
Can interpret metrics such as the Confusion Matrix, Precision, Recall, and F1-Score.	2	3	1	2	3	2	3	-	1	3	3	3
Can explain the concept of the Bias-Variance Tradeoff and the effect of regularization (L1/L2).	2	3	3	3	1	3	3	3	1	1	1	2
Can explain Support Vector Machines (SVM) and the “kernel trick” concept.	2	3	3	3	1	3	1	3	1	2	3	2
Understand concepts such as Information Gain and entropy in Decision Trees.	2	3	3	3	1	2	3	3	2	2	3	3
Implement and compare ensemble models such as Random Forest and Gradient Boosting (XGBoost) using Scikit-learn.	2	3	3	3	1	3	1	3	1	2	3	2