Explores model selection, evaluation, and generalization in machine learning, emphasizing unbiased performance estimation and the risks of over-learning.
Explores data collection, feature selection, model building, and performance evaluation in machine learning, emphasizing feature engineering and model selection.
Explores powder treatment through milling and classification techniques for ceramic production, covering crushing, milling, particle breakage, and powder synthesis.
Delves into Bayesian Knowledge Tracing and Learning Curves, exploring the prediction of student knowledge over time and the importance of accurate performance measurement.
