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sofia-ml-2023-1's Introduction

"Machine Learning" Course

Course prepared for Sofia University: Palo Alto facility, July-September 2023.

News

  • (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

Course program

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 Historical reference.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

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