ml2526_assignments

Assignments for the 'Machine Learning' course at the FU Berlin, winter term 2025/2026.

Course Assignment Guidelines

📚 Weekly Assignment Structure

Each week includes two assignments:

File Format	Required For
assignment[x]_1.ipynb	All students
assignment[x]_2.ipynb	10 ECTS students only

Upload your solution as a .ipynb file AND a .pdf file in the respective entry in the whiteboard. You will find each deadline there as well.

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✅ Grading Requirements

Pass/Fail System

• Each submitted .ipynb notebook receives either a "pass" or "fail" grade
• Minimum # of passes: n-1

Separate Tracking

The n-1 # of passes is tracked separately for each assignment type:

For 5 ECTS Students:

• ✔️ Must achieve n-1 # of passes on assignment[x]_1.ipynb series

For 10 ECTS Students:

• ✔️ Must achieve n-1 # of passes on assignment[x]_1.ipynb series
• ✔️ Must achieve n-1 # of passes on assignment[x]_2.ipynb series

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🌟 BONUS Tasks

• Optional BONUS tasks appear in some notebooks
• Successfully completing BONUS tasks earns extra points toward your final grade
• Check the Whiteboard assignment grading for bonus point confirmations
• 10 ECTS students will find separate bonus tasks in assignment[x]_2.ipynb
• 5 ECTS students will NOT get additional points for solving assignment[x]_2.ipynb Bonus tasks
• Vice Versa: 10 ECTS students will NOT get additional points for solving assignment[x]_1.ipynb Bonus tasks

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📋 Quick Summary

Study Program	Requirements	Pass Criteria
5 ECTS	assignment[x]_1.ipynb	n-1
10 ECTS	assignment[x]_1.ipynb + assignment[x]_2.ipynb	n-1 each
All Students	Optional BONUS tasks	Extra final exam points

Note: The n-1 rule is mandatory to pass the tutorial component of the module.