skbly7

> almost all of the government email IDs are Gmail.

I think you are mistaken.

Majority of the emails are on government server: https://email.gov.in/

They used to be on 3rd party provider till a few years back (but still never on Gmail).

skbly7

4 年前議論

Thanks for creating it and looking forward to try it out.

I have been looking for similar solution and the whitelist used to fail with other tools as they weren't resolving the dependencies.

skbly7

4 年前議論

You can use smart search queries specially for the title/keywords/companies you are interested in.

A sample search will look like this:

- `"python" "engineer" "infrastructure" site:jobs.lever.co`

- `"python" "engineer" "infrastructure" site:boards.greenhouse.io`

(and in the search tools, limit the results to Past week, etc)

Obviously it can only track companies who use tools like lever, greenhouse, etc.

skbly7

4 年前議論

Plus, these plugins to achieve similar functionality: https://meta.discourse.org/t/thoughts-on-a-plugin-which-turn...

skbly7

4 年前議論

In case someone is interested about this domain. There was an interesting challenge around it on AIcrowd last year.

It was called 'Learning to Smell' and hosted by popular swiss fragrance and flavour business Firmenich. It contains publicly available dataset, baselines, winner codebases, etc., to play around with.

[1] https://www.aicrowd.com/challenges/learning-to-smell

[2] https://discourse.aicrowd.com/c/learning-to-smell/357

[3] https://www.aicrowd.com/challenges/learning-to-smell/noteboo...

Disclaimer: I have been affiliated with AIcrowd.

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Dataset containing 54392 real-world Food Images [and computer vision benchmark]

Can you decide which images to label using limited budget? ($20k ML challenge)

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