Erinevus lehekülje "SummerAI" redaktsioonide vahel
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(Uus lehekülg: 'Study materials and assignment instructions. Schedule: TBD Lecturer: Priit Järv == Lecture Slides == * week 1: Introduction * week 2: Machine Learning * week 3: Large Langua...') |
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| 5. rida: | 5. rida: | ||
Lecturer: Priit Järv | Lecturer: Priit Järv | ||
| − | == | + | == Lectures == |
* week 1: Introduction | * week 1: Introduction | ||
| 12. rida: | 12. rida: | ||
* week 4: Technical Aspects of Machine Learning | * week 4: Technical Aspects of Machine Learning | ||
* week 5: Ethics and Impact of AI | * week 5: Ethics and Impact of AI | ||
| + | * week 6: Closed book test | ||
== Assignments == | == Assignments == | ||
Redaktsioon: 26. märts 2024, kell 12:43
Study materials and assignment instructions.
Schedule: TBD
Lecturer: Priit Järv
Lectures
- week 1: Introduction
- week 2: Machine Learning
- week 3: Large Language Models
- week 4: Technical Aspects of Machine Learning
- week 5: Ethics and Impact of AI
- week 6: Closed book test
Assignments
Homework
Complete these as a group, outside the classroom.
Teachable Machine (deadline XX.YY)
Lab Work
Complete these as a group.
For each assigment, write a text file with answers to the questions or results of the lab work. One or more groups will present their results to everyone. There will be a joint discussion.
- Classical Machine Learning (XX.YY)
- Neural Network (XX.YY)
- LLM themed, to be decided (XX.YY)
Submitting results
Where to submit will be clarified before the start of the summer school.
Grading
Your grade will be formed by:
- 50% participation: actively taking part of solving the homework. Will be self-graded.
- 50% written test.