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Note: Schedule is subject to changes and adjustments. Links will get updated and filled in as we go. Slides are linked from each lecture.
Readings: Complete the assigned readings, prior to lecture. The default textbook for this class is Daume, A Course in Machine Learning (CIML); you should read the relevant chapter(s) there first. Additionally, a variety of texts are provided for each topic, many of them available free online. These are usually optional, but the more you read, the better your understanding of the topic.
Hands-on notebooks: On the dates listed as "Hands-on" (in green), please bring your laptop to class. If you are not able to bring a laptop to class, please partner with a friend who is.
Guest lectures: On the dates listed as "Guest lecture" (in blue), you will hear from other researchers in machine learning, robotics, data science, and learning theory. With such a quickly evolving field, it's important to get a very broad view, from a variety of researchers. (Pro-tip: these researchers have agreed to guest lecture in part because they are on the lookout for strong undergrads trained in ML to contribute to their research.)
Books and readings:
Books and readings:
Primary textbook: Daumé: A Course in Machine Learning (CIML).
Additional sources:
- AIMA: Russell and Norvig, "Artificial Intelligence: A Modern Approach.'' 3rd Edition, Prentice Hall, 2010.
- D1: Lecture 1 from Dasgupta's course on Machine Learning
- J1: Lecture 1 from Jaakkola's course on Machine Learning
- Mitchell: Machine Learning, McGraw Hill, 1997.
- KV: Kearns and Vazirani: An Introduction to Computational Learning Theory, MIT Press, 1994.
- CLRS: Introduction to Algorithms (Third Edition), by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Cliff Stein. MIT Press, 2009.
- MR: Motwani and Raghavan, "Randomized Algorithms" Cambridge University Press, 1995.
- FML: Mohri, Rostamizadeh, and Talwalkar: Foundations of Machine Learning, MIT Press, 2012.
- HTF: Hastie, Tibshirani, and Friedman: The Elements of Statistical Learning Second Edition, Springer, 2009.
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