INF554 - Machine and Deep Learning

Information

The Data Science and Mining - Introduction to Machine Learning class will cover the following aspects:

• The Machine Learning pipeline
• Data preprocessing and exploration
• Feature selection/engineering and dimensionality reduction
• Supervised learning
• Unsupervised learning
• Web mining: recommendations, collaborative filtering, opinion/sentiment analysis, web advertising and algorithms
• Learning from graphs: ranking in graphs, ranked lists comparison, learning to rank, community detection and graph clustering, applications

Recommended readings

(my picks)

• Good book to review fundamentals: Mathematics for Machine Learning (Deisenroth et al.)
• Focus on Linear Algebra: Linear Algebra and Learning from Data (Gilbert Strang)
• The “bible” of Deep Learning: Deep Learning (Goodfellow et al.)