Introduction to Machine Learning (6.036)

Sample exercises for helping students think about deploying ML systems in the real world. (These exercises were developed by Kavya Ravichandran and Jacob Andreas.)

• Feature weights in linear models
• Feature correlation and Simpson's paradox
• Adversarial examples
• Reward design and specification gaming
• Bias in word embeddings
• Filter bubbles and feedback loops