NLP in Industry: challenges and best practices
Module Description
| Course | Module Abbreviation | Credit Points |
|---|---|---|
| BA-2010[100%|75%] | CS-CL | 6 LP |
| BA-2010[50%] | BS-CL | 6 LP |
| BA-2010 | AS-CL | 8 LP |
| Master | SS-CL, SS-TAC | 8 LP |
| Lecturer | Daniel Dahlmeier |
| Module Type | |
| Language | English |
| First Session | 24.04.2020 |
| Time and Place | |
| weekly: (24.04.-24.05.) |
Friday, 14:15-15:45, INF 327 / SR 2 (or virtual if required) | block: (10.-14.08) |
daily, 09:15-16:45, INF 306 / SR 13 (or virtual if required) |
| Commitment Period | tbd. |
Modalities
To sign up for the class, send an email to d.dahlmeier at sap.com The class consists of two parts; first weekly meetings on fridays during the summer term, then a week of block sessions mid August.
Prerequisite for Participation
-Mathematical Foundations of CL (or a comparable introductory class to linear algebra and theory of probability) -Programming I (Python)
-Statistical Methods for CL (or a comparable introductory class to machine learning)
Assessment
Inhalt
This seminar focuses on common challenges and best practices for natural language processing (NLP) in industry. NLP in industry comes with its own challenges, like data sparsity, data privacy regulations, and cost-benefit trade-offs. In this seminar, we discuss these challenges and technical approaches to overcome them. The seminar includes a practical project where participants propose a project, implement experiments and present the results to the class.
Module Overview
Agenda
| Date | Session | Materials |
Literature
