Profilierungsmodul Computerlinguistik II
Hinrich Schütze, David Kaumanns
Center for Information and Language Processing, University of Munich
2015-10-13
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Lectures
Wednesday, 09:30-11:00, 131
Basic machine learning (Hinrich Schütze)
Current topics in NLP research (PhD students at LMU)
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Lecturers
Heike Adel
David Kaumanns
Sebastian Ebert
Katharina Kann
Sascha Rothe
Hinrich Schütze
Irina Sergienya
Yadollah Yaghoobzadeh
Wenpeng Yin
Schütze: Text classification & Naive Bayes
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Practical exercise (David Kaumanns)
Wednesday, 11:00-11:45, 131
Introduction to Torch
Help with programming projects
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Languages
German (most lectures)
English (most slides, talks by non-German speaking PhD
students)
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Prüfungsform: Programmieraufgabe
Eine Programmieraufgabe beinhaltet den Entwurf eines
Algorithmus und dessen Implementierung in elektronischer Form.
Das Programm ist schriftlich zu dokumentieren.
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Prüfungsform: Programmieraufgabe
Eine Programmieraufgabe beinhaltet den Entwurf eines
Algorithmus und dessen Implementierung in elektronischer Form.
Das Programm ist schriftlich zu dokumentieren.
Project advisors:
Heike Adel
Sebastian Ebert
Katharina Kann
Hinrich Schütze
Irina Sergienya
Yadollah Yaghoobzadeh
Wenpeng Yin
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Schedule
15.11.: Select project
16.11.-26.01.: Work on project
27.1. / 3.2.: Give a talk about your project (15 minutes)
Your project is due Jan 29.
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Home page of the class:
www.cis.lmu.de/~ hs/teach/15w/pmclii/
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Inverted classroom
Each week watch one or two lectures of Andrew Ng’s machine
learning introduction on Coursera.
We will discuss these lectures in the first 5-10 minutes of each
class.
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Programming project 1 (Schütze)
Familiarize yourself with an existing code base for keyword in
context search (piggyback)
Add the following feature: the contexts can be clustered and
presented in clustered form to the user based on a number of
clustering criteria
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