Dear student,

We hope you have enjoyed this course which offers an introduction to Unsupervised Learning, Reinforcement Learning & Neural Networks. By now, you should be able to:

• Describe the main classes of clustering techniques
• Implement k-means and hierarchical clustering
• Motivate the need and choice of dimensionality reduction techniques
• Implement Principal Component Analysis (PCA) for feature extraction
• Explain how deep neural networks work and their advantages
• Train deep neural networks for classification and regression tasks
• Explain the basic concepts and techniques of reinforcement learning
• Describe how reinforcement learning could be applied in real world applications

Best,

Tom Viering, also on behalf of all other lecturers