Applied Machine Learning Project Presentations

Student project presentations from the course Info 251. Applied Machine Learning.

Each student group applies their mastery of machine learning to a different original dataset, to answer an interesting and novel question. Each group will give a short “lightning presentation”. Projects include:

• What makes a song popular?
• Using deep learning to find your celebrity parents
• Identifying manipulated air quality reports in China
• Who gets the L1 visa?
• Predicting the lifetime of a San Francisco bike share bicycle
• Why do asthmatics stop using their inhalers?
• Investigating the predictive​​ power of eye tracking data in observer-actor pairs
• Pathways to higher salaries in India
• Targeting customer attrition in a Chilean bank
• Predicting day-ahead electricity prices in the California electricity grid
• Opportunities for arbitrage in the Beijing housing market
• Anticipating edits on Wikipedia
• Determinants of medication switching for in-patient diabetics
• Predicting air quality in urban environments

The course provides a theoretical and practical introduction to modern techniques in applied machine learning. It covers key concepts in supervised and unsupervised machine learning, including the design of machine learning experiments, algorithms for prediction and inference, optimization, and evaluation. Students learn functional, procedural, and statistical programming techniques for working with real-world data.