Problem Set 2

The pre-proposal happens here

Problem 3 of PS2 is the first piece of your final project, and it is sharpened here in conversation before you post it. Problems 0, 1 and 2 are on ml4science.com and go to Moodle as usual.

Problem 3: Project Pre-Proposal

20 points. One page, five things, written before you open this conversation.

The five things
  • State of the field. Where scientific machine learning is, and what caught you
  • Problem. What system, what data, what question
  • Hypothesis and evidence. One testable claim, two to four references that make it plausible
  • Plan. The data, the first method, and how you would know it worked
  • Why it matters. A short paragraph
Where drafts usually fail
  • A topic instead of a question: interesting area, nothing that could come out false
  • A hypothesis no experiment in the plan could test
  • Data named in the abstract, with no path to actually getting it
  • References that sound supportive but were never read past the abstract

Finding a dataset is usually easier than finding an idea. If you are stuck, start from data you can actually get and let the question grow from it.

Write it first, then paste it

  • The draft is yours. Write the page before you open the conversation. The agent will not write it for you, and asking it to will cost you the marks this problem is made of.
  • It will push back. On where the evidence is thin, whether the problem is well posed, and whether your plan could actually test your hypothesis.
  • Argue. It is often wrong about your field. Say so, and hold the position you can defend.
  • Paste revisions, do not describe them. When you rewrite a section, paste the new words in. It reads the recent conversation, not an archive of it.
  • It can search, and it will. When a claim about the literature matters, it looks it up and tells you what it found. It will still ask what the paper measured and what it did not show, which is the part only you can answer.
  • Then post. The revised page goes on #ddm_project, ending with one or two sentences on what the exchange changed your mind about.

What a good exchange looks like

The mark is not for a smooth proposal. It is for a proposal that survived being argued with, and for knowing which parts did not survive.

  • Defend the question, not the topic. If you cannot say what result would make you abandon the hypothesis, you have a topic.
  • Bring the reference, not the impression. When it asks what a paper actually showed, answer from the paper.
  • Let the scope shrink. Most first drafts are three projects. The useful outcome is often one of them, done properly.
  • Keep what you disagreed with. Those sentences are the ones worth writing up at the end of your post.

Then it goes to Slack

Post the revised page on #ddm_project. Read two other people's while you are there: the projects that go well are usually the ones that found a neighbour early.

Found a bug or a badly worded question? Use the comment button at the top right. It goes straight to a list I read.