Teaching Coordinator, Lab assistant (36 hours - autumn 2022).

Contents

• General Introduction to Machine Learning
• Supervised/Unsupervised Learning (Naive Bayes, KNN, regression, trees, clustering)
• Advanced Machine Learning Concepts (regularization, feature selection)
• Kernels (SVMs)
• Introduction to Neural Networks
• Deep Learning (RNNs, CNNs, NLP)
• Machine & Deep Learning for Graphs (graph kernels, GNNs)