lecturer: Jakab Buda

date (8*90 min): 

• 18/02/2022 - 2 p.m
• 25/02/2022 - 2 p.m
• 04/03/2022 - 2 p.m
• 18/03/2022 - 2 p.m
• 25/03/2022 - 2 p.m
• 01/04/2022 - 2 p.m
• 08/04/2022 - 2 p.m
• 22/04/2022 - 2 p.m

location: ONLINE

ZOOM:  We will send the Zoom link in e-mail. 

language: English

max. 20 person

1.Introduction

• usage
• different methods
• steps of ML projects
• cost function
• parameters, hyperparameters
• performance metrics

2. Data and project ideas

3. Data preparation

4. regular ML methods I - regression

5. regular ML methods I - classification

• logistic / multinomial regression; SVM; Decision tree

6.  ensemble methods

• Stacking
• Random Forest
• XGBoost

7. Neural nets I – structure

8. Neural nets II – tuning