Case Study

Decide whether a PhD student pursuing a novel publishable method should follow the basic-system advice.

Case context: A PhD student is designing a project whose primary goal is to develop a novel algorithm suitable for publication at a top research venue. A labmate suggests they quickly build a basic system and iterate using error analysis, citing general machine learning best practices.

Question: Based on the source's stated audience for this advice, should the PhD student follow the basic-system advice as given, and why or why not?

Sample answer: According to the source, the basic-system advice is meant for readers building AI applications, not those aiming to publish academic papers. Since the PhD student's primary goal is producing a novel, publishable method, this specific advice as framed by the source is not necessarily intended for their situation. The student should recognize that the author explicitly separates this guidance from research goals and plans to address research separately.

Key points:

  • Advice targets AI-application builders, not academic researchers
  • Student's goal is publishable research, not application building
  • Source explicitly separates the two audiences
  • Author states research will be addressed later
  • Conclusion should reflect the audience mismatch

Rubric: Full credit: correctly identifies that the advice targets application builders, notes the student's goal is research-oriented, and concludes the advice is not the source's intended fit while acknowledging the author defers research advice. Partial credit: identifies the mismatch without full explanation.

0

1

Updated 2026-07-10

Contributors are:

Who are from:

Tags

Machine Learning

Deep Learning

Machine Learning Strategy

Supervised Learning

Dive into Deep Learning @ D2L

Data Science

Machine Learning Yearning @ DeepLearning.AI