Open University

Tampere

Statistical Methods for Text Data Analysis, Lectures

Contact information Email: open.studies.tau [at] tuni.fi Phone: 0294 520 200More information concerning Open University studies <a href="https://www.tuni.fi/open-university">tuni.fi/open-university</a>

Advanced studies

Faculty of Information Technology and Communication Sciences

Technology and Natural Sciences

Apply for Open University studies by using the following links:<ul><li><a href="https://tau-avoin.ilmoittaudu.fi/lobby/?realization=J-otm-786efc6c-8aad-44c4-a7f1-c39167a947b6_2023-tampere-DATASTAT840" target="_blank">DATA.STAT.840 Statistical Methods for Text Data Analysis, lectures, Tampere</a></li></ul>You can find a link to the Open University Admissions service and application instructions on the <a href="https://www.tuni.fi/en/study-with-us/open-higher-education-studies/open-university/applying-open-university">Applying to Open University studies</a> page.Some of the studies require prior studies. For example, studying intermediate studies may require some completed basic studies. These are described on the Information about studies tab of the study unit under prior requirements.When you have been admitted to the studies, you must enrol separately via the Sisu information system for the implementation of the unit of study and, for example if set, for a practise group of your choice. You will receive instructions on how to do this by e-mail after you have confirmed your acceptance of the study place by paying the required fee.

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City Centre Campus

Contact teaching

Look information at <a href="https://www.tuni.fi/en/study-with-us/open-higher-education-studies/open-university/applying-open-university">Applying to Open University studies</a>.

This course teaches various statistical methods for modeling and &nbsp;analysing text data. Contents are planned to include models for &nbsp;representing text including vector space models and neural embedding &nbsp;models; document content processing stages such as lemmatization and &nbsp;keyphrase extraction; probabilistic models of content variation &nbsp;including n-grams and topic models; and methods for various text &nbsp;analysis tasks. The course is in development and detailed contents will &nbsp;be updated.

<h2>Common</h2><h3>Lecture: </h3>29.08.2023 14:00 - 16:00, TAU Pinni B1096 auditorio (100) 05.09.2023 14:00 - 16:00, TAU Pinni B1096 auditorio (100) 12.09.2023 14:00 - 16:00, TAU Pinni B1096 auditorio (100) 19.09.2023 14:00 - 16:00, TAU Pinni B1096 auditorio (100) 26.09.2023 14:00 - 16:00, TAU Pinni B1096 auditorio (100) 03.10.2023 14:00 - 16:00, TAU Pinni B1096 auditorio (100) 10.10.2023 14:00 - 16:00, TAU Pinni B1096 auditorio (100) 24.10.2023 14:00 - 16:00, TAU Pinni B1096 auditorio (100) 31.10.2023 14:00 - 16:00, TAU Pinni B1096 auditorio (100) 07.11.2023 14:00 - 16:00, TAU Pinni B1096 auditorio (100) 14.11.2023 14:00 - 16:00, TAU Pinni B1096 auditorio (100) 21.11.2023 14:00 - 16:00, TAU Pinni B1096 auditorio (100) 28.11.2023 14:00 - 16:00, TAU Pinni B1096 auditorio (100) 05.12.2023 14:00 - 16:00, TAU Pinni B1096 auditorio (100)

The student is familiar with document representation, modeling, and &nbsp;analysis techniques and can apply several basic techniques in text &nbsp;analysis tasks.

<h2>Prerequisites</h2>basic probability courses; familiarity with programming in R, Matlab or Python

Lecture slides and exercise packs are provided during the course.

Statistical Methods for Text Data Analysis, Lectures

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Statistical Methods for Text Data Analysis, 5 cr

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Statistical Methods for Text Data Analysis, Lectures