Recap regarding the "acting rationally" paradigm; optimization in machine learning; simple optimization-based approaches (linear+polynomial regression, gradient descent, logistic regression); batch, incremental, mini-batch approach
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;
A set of colab notebooks, regarding especially these topics:
– Gradient descent on a regular and an elongated surface;
– Linear, polynomial and logistic regression;
– Optimization-based regression in Python using SciPy;
– ...
The estimated additional time required for studying the material independently, using the lecture videos/slides and also referencing other literature and material, as necessary. Facilitates correct understanding of the material.
This activity also includes the time required for review before exams.
Quiz activities meant to provide quick, unassessed feedback to students regarding their grasp of the material.
