Machine Learning PhD course (April 2016)
- Lecture 1 (Basic concepts and Introduction to Artificial Neural Networks)
- Lecture 2 (Deep Learning I: Energy Based Models, Auto-Encoders, Tricks of the Trade)
- Lecture 3 (Deep Learning II: Convolutional Neural Networks, Language Models, Word Embeddings)
- Lecture 4 (Deep Learning III: Recurrent Neural Networks, Applications, Ongoing Research and Open Issues)
- Lecture 5 (Kernel Machines)
- Lecture 6 (Statistical Relational Learning)