Lecture
Model Assessment: Metrics and Selection
Related lectures (35)
Logistic Regression: Fundamentals and Applications
Explores logistic regression fundamentals, including cost functions, regularization, and classification boundaries, with practical examples using scikit-learn.
Image Classification: Overfitting and Accuracy Measures
Explores overfitting and accuracy measures in image classification, emphasizing the importance of model generalization and optimal accuracy.
Assumption of Machine LearningMOOC: IoT Systems and Industrial Applications with Design Thinking
Explores the philosophy of machine learning and the importance of smoothness assumptions in training sets.
The design problemMOOC: Digital Signal Processing I
Covers the design of a communication system using the old digital paradigm.
Equivalent Degrees of Freedom in Spline Smoothing
Explores equivalent degrees of freedom in spline smoothing and the bias-variance tradeoff in fitting data.