06 Deep Learning 1: Neural networks, Convolutional layers (MLVU2018) @riskone1

06 Deep Learning 1: Neural networks, Convolutional layers (MLVU2018) @riskone1

Uploaded February 2018 | Updated September 2026, 3 days ago

In this lecture we dive into the world of neural networks and deep learning. Lecturer: Peter Bloem. See the PDF for image credits.

slides: dropbox.com/s/qku3ng5mum87z8h/32.DeepLearning1.annotated.pdf?dl=0

06 Deep Learning 1: Neural networks, Convolutional layers (MLVU2018)

5 Probability 1: Logistic regression, Log loss, Entropy (MLVU2020)

MLVU 8.2: Maximum likelihood estimators

10 Tree Models and Ensembles: Decision Trees, AdaBoost, Gradient Boosting (MLVU2019)

MLVU 10.4: Boosting: Adaboost and gradient boosting

MLVU 5.5: Information theory

MLVU 11.2: Deep learning on sequences

MLVU 1.2 Classification

MLVU 3.2: Model evaluation

03 Methodology 1: ROC curves, Ranking classifiers (MLVU2018)

MLVU 2.2 Searching for a good model

MLVU 6.2: Local and global derivatives

06 Deep Learning 1: Neural networks, Convolutional layers (MLVU2018)