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https://github.com/scienxlab/checklists

Checklists for scientists and engineers
https://github.com/scienxlab/checklists

checklists machine-learning scientific-computing

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Checklists for scientists and engineers

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# ☑️ checklists

A collection of checklists, lists, and decision trees for scientists and engineers.

The checklists are maintained as [Markdown](https://www.markdownguide.org/) files for convenience, but can be rendered in other formats using conversion tools like [pandoc](https://pandoc.org/). For example, to render the `machine-learning-review` checklist as a PDF, you can do this:

```shell
pandoc -t html --css style.css \
-V margin-top=7 -V margin-right=10 \
-V margin-bottom=7 -V margin-left=10 \
machine-learning-review.md -o out.pdf
```

You can install `pandoc` on Ubuntu with `sudo apt install pandoc`; builds exist for most distros. To use the command above, you may also need to install the `wkhtmltopdf` tool as well.

In the near future, we will provide PDFs via links from this repository.

## Contents

- [`machine-learning-pitfalls`](./machine-learning-pitfalls.md) — ✨ NEW ✨ A non-exhaustive list of pitfalls in planning, executing and implementing machine learning projects.
- [`machine-learning-review`](./machine-learning-review.md) — Annotated checklist for people running or reviewing machine learning projects. Originally published in [this blog post](https://agilescientific.com/blog/2019/4/9/machine-learning-project-review-checklist).
- [`machine-learning-planning`](./machine-learning-planning.md) — Annotated checklist specifically for earth scientists planning machine learning projects.
- [`reproducible-science-projects`](./reproducible-science-projects.md) — An aspirational wishlist for open source and reproducible scientific repos.

## Coming soon

- Open data checklist
- Benchmark dataset checklist
- Scientific presentation checklist
- Computing course checklist
- Hackathon planning checklist
- Which programming language should I learn first?
- So you want to build a Python app?