Content:
– A recap on the "acting rationally" AI paradigm;
– What optimization is;
– How it is used in machine learning, minimizing a loss function, etc.;
– Simple optimization-based approaches:
– Linear regression;
– Polynomial regression;
– Gradient descent;
– Logistic regression;
– Batch, incremental and mini-batch learning;
