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Seminar/Practical Work/Thesis at Institute for Machine Learning

Seminar/Practical Work/Thesis at Institute for Machine Learning

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Which properties should a good paragraph have, according to the lecture? (Select all that apply)

Self-contained treatment of one idea

Coherent

As long as possible

Unified

Distinct

What does the lecture describe as the key feature of 'free writing'?

Writing perfectly formatted sentences on the first try

❌

Avoiding any use of editing tools

❌

Writing through interruptions (e.g., missing references/words) without worrying about grammar, formatting, or flow, then polishing later

✅

Only writing the abstract first

❌

Writing exclusively in passive voice

❌

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Which strategies are suggested in the lecture to encourage writing discipline? (Select all that apply)

Environment

✅

Quotas / internal deadlines

✅

Scheduling

✅

Avoiding all feedback until submission

Writing logs

Timing

Which behavioral challenges are explicitly listed in the lecture as common obstacles to writing? (Select all that apply)

Fear of criticism

Distraction

Overconfidence

Avoidance

Feeling stuck

Perfectionism

Which of the following are listed among the '5 Elements for Consideration' when discussing results? (Select all that apply)

Future Directions

Context

Weaknesses

Broader Impact

Funding Sources

Interpretation

The lecture states ML Experiments are approximately equal to which combination from the IMRaD framework?

Results + Limitations only

❌

Abstract + Conclusion

❌

Introduction + Methods

❌

Methods + Related Work

❌

(Methods) + Results + Discussion

✅

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According to the 'modern approach' described in the lecture, what is the main purpose of the Methods section?

To list all software versions used

❌

To restate the abstract in more detail

❌

To include every single detail needed to exactly reproduce the work

❌

To present the results of experiments

❌

To establish the credibility of the approach used to solve the problem identified in the introduction

✅

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What is the stated purpose of the Related Work section?

To provide raw data tables

❌

To show how your research builds on or differs from existing studies

✅

To replace the need for an introduction

❌

To list every paper ever published on the topic

❌

To advertise the authors' other papers

❌

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Which pieces of advice does the lecture give about writing Related Work? (Select all that apply)

Highlight key differences to your own work

✅

Avoid citing anything older than one year

❌

Be concise and critical

✅

Write it as a comprehensive review of the whole field

❌

Stay relevant: focus on closely related, up-to-date studies

✅

Organize by theme

✅

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For a Bachelor/Master thesis at the IML, the lecture recommends following the structure of:

A patent application

A grant proposal

A textbook chapter

A newspaper article

A typical machine learning conference paper, with more comprehensive Introduction/Background/Related Work

✅

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