WiSe 17/18: Seminar: Mathematics of Data Science
Shane Kelly
Zusätzl. Angaben / Voraussetzungen
Aimed at: Bachelor and masters students (of mathematics, statistics, computer science, physics, etc).
Background: Students should know basic probability (expected values, variance, standard deviation, binomial distribution, normal distribution). Easy derivatives and integrals may appear in some talks, and matrix multiplication may appear in some talks.
SchließenKommentar
Harvard Business Review called Data Scientist "The Sexiest Job of the 21st Century", and indeed, the field of data science is evolving into one of the fastest-growing and most in-demand disciplines in the world. The enhanced ability to observe, collect and store data in settings from business to government, health care to academia, promises to revolutionise these industries.
In this seminar, we will cover some of the mathematical foundations of data science.
Topics will be chosen by the students from among the following (there will be multiple lectures per topic):
Machine Learning, Clustering, Belief Propagation, Compressed Sensing, Topic Models, Hidden Markov Process, Graphical Models, High Dimensional Probability, Random Graphs.
For more information see: http://www.mi.fu-berlin.de/users/shanekelly/MoDS2017-18WS.html
SchließenLiteraturhinweise
Course text: "Foundations of Data Science", Avrim Blum, John Hopcroft, and Ravindran Kannan
16 Termine
Regelmäßige Termine der Lehrveranstaltung