01 Introduction to Machine Learning (MLVU2018) @riskone1

01 Introduction to Machine Learning (MLVU2018) @riskone1

Uploaded February 2018 | Updated September 2026, 5 days ago

Lecture 1 in the Machine Learning course at the VU University Amsterdam. Lecturer: Peter Bloem. See the PDF for image credits.

Slides: dropbox.com/s/g9rhjrnl8hty06x/11.Introduction.annotated.pdf?dl=0

01 Introduction to Machine Learning (MLVU2018)

MLVU 7.3: Convolutions

9 Deep Learning 2: Generative models, GANs, Variational Autoencoders (VAEs) (MLVU2019)

MLVU 10.3: Ensembling: stacking, bagging and random forests

MLVU 5.1: Introduction to probability

09 Deep Learning 2: GANs, Variational Autoencoders (MLVU2018)

4 Methodology for pre-processing, PCA, Eigenfaces (MLVU2020)

MLVU 3.5: Statistics for Machine Learning Experiments

MLVU 8.3: Expectation-maximization

05 Probabilistic Models 1: Naive Bayes, Entropy, Logistic Regression (MLVU2018)

MLVU 6.1: Neural networks

7 Deep Learning: tensor backpropagation, convolutional layers (MLVU2020)

01 Introduction to Machine Learning (MLVU2018)