(Applied Machine Learning)
- Introduction to ML
- رگرسیون خطی
- Multivariate regression / Bias-variance Tradeoff
- regularization and normal equation
- k-nearest neighbors and evaluation metrics for classification
- Decision trees
- Bayes classifier and naive Bayes
- neural networks
- Support vector machines
- ensemble methods
- unsupervised learning
- clustering
- Dimensionality reduction
- evolutionary algorithms