| Description |
Teaching assistant(s):
- Vasilis Dedousis
- August Blomgren
- Pia Koller
Prerequisites:
None
Required material or equipment:
Laptop or other computer system
Textbook(s):
- Deisenroth, M. P., Faisal, A. A., & Ong, C. S. (2020) Mathematics for Machine Learning. Cambridge University Press , Cambridge, UK..
Recommended textbooks:
- Strang, G. (2016). Introduction to Linear Algebra (5th ed.). Wellesley-Cambridge Press, Wellesley, MA, USA.
- Spivak, M. (2008). Calculus (4th ed.). Publish or Perish, Houston, TX, USA.
- Bertsekas, D. P., & Tsitsiklis, J. N. (2008). Introduction to Probability (2nd ed.). Athena Scientific, Belmont, MA, USA.
- Wasserman, L. (2004). All of Statistics: A Concise Course in Statistical Inference. Springer, New York, NY, USA.
- Boyd, S., & Vandenberghe, L. (2004). Convex Optimization. Cambridge University Press, Cambridge, UK.
- VanderPlas, J. (2016). Python Data Science Handbook: Essential Tools for Working with Data. O'Reilly Media, Sebastopol, CA, USA.
Course policies and classroom rules of conduct:
- Academic dishonesty, plagiarism, and any other kind of fraud will lead to the exclusion from the course.
- Attendance required
- Punctuality
- Homework and project must be handed on time |
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