Objectives
After completing the course, the student will be able to
- Explain several different language technology applications
- Analyze the most important characteristics of human language as a data source
- Select or create a suitable annotated text corpus for the given task
- Discuss the basic feature representations of language data in machine learning applications
- Implement a simple machine learning pipeline for the given language technology application
- Explain the idea behind semantic vector spaces and summarize the main methods used to learn meaningful vector spaces
After completing the course, the student will be able to
- Explain several different language technology applications
- Analyze the most important characteristics of human language as a data source
- Select or create a suitable annotated text corpus for the given task
- Discuss the basic feature representations of language data in machine learning applications
- Implement a simple machine learning pipeline for the given language technology application
- Explain the idea behind semantic vector spaces and summarize the main methods used to learn meaningful vector spaces
- Peppi-Teacher: Filip Ginter
- Peppi-Teacher: Jenna Kanerva