Διαλέξεις

Top-level directory

• 01. Εισαγωγή

  • 01. Εισαγωγή.pdf

• 02. Supervised Learning - Perceptron

  • MLapplications.pdf

  • NN-ICS_1.pdf

  • Supervised_Learning.pdf

• 03. Regression - Clustering - DT

  • 01. Regression - Perceptron.pdf

  • 02. Εlbow method - Aξιολόγηση Clustering.ipynb

  • 02. Clustering.pdf

  • 03. Gaussian Mixture Models EM.pdf

  • 04. Decision Trees - Titanic Dataset.ipynb

  • 04. Decision Trees.pdf

  • πρόσθετο υλικό kMeans Convexity.pdf

• 04. Multi-Layer Perceptron

  • 04. FFNN - Automatic Differentiation.pdf

  • 04. MLP - Backpropagation.pdf

  • 04. NN - SGD - Computational Graphs - Backpropagation.pdf

• 05. PAC Learning

  • 05. PAC Learning - finite hypothesis class.pdf

• 06. Support Vector Machines

  • 06. Support Vector Machines.pdf

• 07. Rademacher Complexity. The Infinite Hypothesis Case

  • 07.1 Rademacher Complexity - the Infinite Hypothesis Case.pdf

  • 07.2 Pseudo-Dimension of Regression.pdf

  • Hans Rademacher, Otto Toeplitz - The enjoyment of mathematics .djvu

• 09.Intro Deep Learning

  • DLresnet.pdf

  • NN_DL.pdf

• 10. Online Learning

  • 09. Online Learning.pdf

  • Chapter 8 - Online Learning.pdf

• 11. Reinforcement Learning

  • RL.pdf

• 12. Boosting

  • 12. Boosting.pdf

  • Chapter 7 - Boosting.pdf

  • errata.txt

• 13. Multiclass Classification - Ranking

  • multi-class classification.pdf

  • ranking.pdf

• 14. Kernel Methods

  • 14. Kernel Methods.pdf

  • Chapter 6 - Kernel Methods.pdf

  • Chapter 16 - Kernel Methods.pdf

  • Sections 11.3.2-11.3.3.pdf