All the models that we have covered in this book up to now were based on the supervised learning paradigm; the training dataset included the input and the desired label of that input. This chapter, in contrast, focuses on the unsupervised learning paradigm. The chapter will include the following topics:

• Principal component analysis
• k-means clustering
• Self-organizing maps
• Restricted Boltzmann Machine
• Recommender system using RBM
• DBN for Emotion Detection