Course prepared for Sofia University: Palo Alto facility, July-September 2023.
- (2023-09-09) Lecture03 has been added + Final Exam!
- (2023-08-12) Lecture02 has been added
- (2023-07-23) Lecture01 has been added
- (2023-07-22) First onground session in Palo Alto
- (2023-07-22) Repo has been created
| N | Lecture | Desctription |
|---|---|---|
| 01 | Introduction, Supervised Learning, and Overfitting | Introduction. Course logistics and syllabus. Historical reference. Setting of basic machine learning tasks. ML models testing, cross-validation. Error decomposition, underfitting and overfitting |
| 02 | Regression. Classifier metrics | Non-parametric Regression. Bias-Variance trade-off for k-NN Regression. Linear Regression. ML and MAP Principles. Least Squares Method. Ridge, LASSO and Elastic Net Regressions. Regression Metrics. Classification Metrics and Confusion Matrix. ROC and AUC. Precision and Recall. Multi-class case |
| 03 | Exam and AI Hype | Exam information. Exam topics. AI/ML/DL "buzzwords" / hype |