The course package covers foundations and recent advances of machine learning techniques, including:
● Basic concepts: Linear regression, nearest neighbour, parametric vs.
non-parametric methods, Bayesian classifiers, the curse of
dimensionality, model accuracy, bias-variance trade-off
● Linear classifiers: linear regression for classification (discriminative
model), linear...
The course package covers foundations and recent advances of machine learning techniques, including:
● Basic concepts: Linear regression, nearest neighbour, parametric vs.
non-parametric methods, Bayesian classifiers, the curse of
dimensionality, model accuracy, bias-variance trade-off
● Linear classifiers: linear regression for classification (discriminative
model), linear...
The course package covers foundations and recent advances of machine learning techniques, including:
● Basic concepts: Linear regression, nearest neighbour, parametric vs.
non-parametric methods, Bayesian classifiers, the curse of
dimensionality, model accuracy, bias-variance trade-off
● Linear classifiers: linear regression for classification (discriminative
model), linear...
The course package covers foundations and recent advances of machine learning techniques, including:
● Basic concepts: Linear regression, nearest neighbour, parametric vs.
non-parametric methods, Bayesian classifiers, the curse of
dimensionality, model accuracy, bias-variance trade-off
● Linear classifiers: linear regression for classification (discriminative
model), linear...
