Lectures

8.3368 Practical Seminar: Machine Learning for Natural Language Processing (KOGW-MWPM-CL, KOGW-MWPM-KI)

Bechberger

Type Language Semester Credits Hours Room Time Term Year
S e 8 4 Di 12-14, Di 14-16 W 2018
MSc: Major subject
MSc major: Linguistics and Computational Linguistics
MSc major: Artificial Intelligence

Syllabus:

Prerequisites: This seminar is targeted at Master students with a background in machine learning and prior knowledge about natural language processing. As we will program small NLP systems from scratch, programming skills (preferably in python) are absolutely required.

In this practical seminar, we will use machine learning techniques to solve challenging NLP tasks, for example, information retrieval and news recommendation. We will use a collection of preprocessed news articles (https://knowledgestore.fbk.eu/) as a data base for our work, which will be based on individual projects conducted by small teams. We will go through the complete research cycle of machine learning, starting with problem definition and data collection, going through steps like feature extraction and hyperparameter optimization, and ending with an evaluation and the interpretation of the evaluation results. At each step, we will both rehearse theoretical knowledge and apply it practically to our projects by implementing the respective step. Grades will be mostly based on weekly documentations about how the different steps were implemented in your own project.

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