Digicampus
Seminar: Machine Learning in Health Care - Details
Sie sind nicht in Stud.IP angemeldet.
Lehrveranstaltung wird online/digital abgehalten.

Allgemeine Informationen

Veranstaltungsname Seminar: Machine Learning in Health Care
Semester SS 2019
Aktuelle Anzahl der Teilnehmenden 3
erwartete Teilnehmendenanzahl 9
Heimat-Einrichtung Prof. Dr. Jens Brunner - Health Care Operations / Health Information Management
Veranstaltungstyp Seminar in der Kategorie Lehre
Erster Termin Donnerstag, 02.05.2019 15:45 - 19:00, Ort: (CIP 2113)
Teilnehmende The course is limited to 9 students. Therefore an application is necessary. Please register for the course on Digicampus and send the completed Excel document (available here: https://megastore.uni-augsburg.de/get/_9eXjKFBGF/ ) as well as a current transcript of records (STUDIS-Notenauszug) to julian.schiele@unikat.uni-augsburg.de until 28-Apr-2019 (11:59 pm). We will inform you whether or not you can attend the course until Tuesday April 30th.
Voraussetzungen (Advanced) Knowledge in mathematics, particularly linear algebra and stochastics; knowledge of a programming language (e.g. Python) is beneficial; interest in health care applications and team work.
Lernorganisation The seminar comprises six sessions (attendance is mandatory) and assignments to each lecture.
Leistungsnachweis Programming assignments, quizzes, group presentations, individual presentations, oral exam.
Online/Digitale Veranstaltung Veranstaltung wird online/digital abgehalten.
Hauptunterrichtssprache englisch
Literaturhinweise - Christopher M. Bishop: Pattern Recognition and Machine Learning. Springer Verlag, 2006.
- Andrew Ng: Machine Learning. Stanford University. Online on Coursera: https://www.coursera.org/learn/machine-learning
- Google Developers: Machine Learning Crash Course. Online: https://developers.google.com/machine-learning/crash-course
- Prashant Natarajan, John C. Frenzel, Detlev H. Smaltz: Demystifying Big Data and Machine Learning for Healthcare. CRC Press, 2017.
- Stephen Boyd: Introduction to Applied Linear Algebra - Vectors, Matrices, and Least Squares. Cambridge University Press, 2017. Online: http://vmls-book.stanford.edu/vmls.pdf
- Barry M. Wise, Neal B. Gallagher: An Introduction to Linear Algebra. Online: http://www.eigenvector.com/Docs/LinAlg.pdf
- Eric Matthes: Python Crash Course. No Starch Press, 2016.
- Official Python tutorial. Online: https://docs.python.org/3/tutorial
- Interactive Python tutorial. Online: https://www.learnpython.org/
- Other literature will be announced in the course.
Sonstiges The course is limited to 9 students. Therefore an application is necessary. Please register for the course on Digicampus and send the completed Excel document (available here: https://megastore.uni-augsburg.de/get/_9eXjKFBGF/ ) as well as a current transcript of records (STUDIS-Notenauszug) to julian.schiele@unikat.uni-augsburg.de until 28-Apr-2019 (11:59 pm). We will inform you whether or not you can attend the course until Tuesday April 30th.
ECTS-Punkte 6

Räume und Zeiten

(CIP 2113)
Donnerstag, 02.05.2019, Donnerstag, 09.05.2019, Donnerstag, 23.05.2019, Donnerstag, 06.06.2019, Donnerstag, 27.06.2019, Donnerstag, 11.07.2019 15:45 - 19:00
(Optional)
Donnerstag, 16.05.2019, Donnerstag, 13.06.2019, Donnerstag, 04.07.2019 15:45 - 19:00

Kommentar/Beschreibung

Topics of the module include (but are not limited to) the following:
- Introduction to Machine Learning
- Programming in Python
- Linear regression
- Logistic regression
- Regularization
- Neural networks
- Support vector machines
- Unsupervised learning
- Insights into up-to-date research and applications

Anmelderegeln

Diese Veranstaltung gehört zum Anmeldeset "Scheduled admission: Machine Learning in Health Care".
Folgende Regeln gelten für die Anmeldung:
  • Die Anmeldung ist möglich von 07.03.2019, 00:00 bis 28.04.2019, 23:59.

Anmeldemodus

Die Auswahl der Teilnehmenden wird nach der Eintragung manuell vorgenommen.

The course is limited to 9 students. Therefore an application is necessary. Please register for the course on Digicampus and send the completed Excel document (available here: https://megastore.uni-augsburg.de/get/_9eXjKFBGF/ ) as well as a current transcript of records (STUDIS-Notenauszug) to julian.schiele@unikat.uni-augsburg.de until 28-Apr-2019 (11:59 pm). We will inform you whether or not you can attend the course until Tuesday April 30th.