Tutorial on deep learning and applications in non-cognitive domains

In Dec 2016, I delivered a tutorial on deep learning and its applications in non-cognitive domains at AusDM'16. It covers:

• Basic concepts of deep learning: best practices in machine learning, three architectures (feedforward, recurrent and convolutional nets), enablers of deep learning (adaptive stochastic gradient, skip-connections, gating, dropouts).
• Current practices in data mining: programming frameworks, tricks of the trade, case-studies in non-cognitive domains (healthcare, software engineering & anomaly detection). 
• Advanced topics for research: deep learning in relational domains, unsupervised learning, memory & attention, how to position yourself in this highly dynamic game.

The materials are accessible here.