Hi...
>and resuming running notebooks whose frontend was closed.
The platform schedules the notebooks, runs them, and saves the results with the output[0]. You can still check the progress, status, and position in the queue of the notebook if you wish. You still get the results after it's done even if you had closed the browser.
>Are you building a product that you plan to release? Or are these contributions that are available as open source components?
Well... We're a machine learning shop, present in Algiers, Algeria and Paris, France, that's been building custom turn-key products for large organizations for quite some time. As you know, non-trivial projects with real stakes are a bit more "challenging" than portfolio projects. Tracking rationale of projects, tracking metrics/params/models, shared access to data, deploying and managing models, challenges in collaboration, setting an environment and keeping things from breaking, or needing a beefy machine.
We started building the platform to allow our teammates to remotely work on projects involving machine learning, as commuting is hard and having contributors in different countries can be challenging. We also wanted to simplify access to a larger talent pool from other countries, which means we had to have a way to work together. We also wanted self-service: our data scientists had to sollicit the help of other engineers to either use some language specific feature, or to deploy their notebooks. We wanted to allow them to do so themselves in one click so they don't wait, and other engineers can work on other things. We wanted the results to get as soon as possible to the domain expert, and allo that domain expert to be able to train models themselves with no code experience, by exposing parameters that are relevant to some sector, and allow them too to deploy a model. In many cases, a domain expert would chime in to tell us that some variable that was dismissed was actually critical at some point in a decision-making process. So we wanted that, too.
We also wanted developers to interact with the models with HTTP requests period. We kind of suffered from having too many simultaneous projects with different stacks.
We needed a way to execute projects efficiently and effectively, but we didn't like other products. We also wanted extensibility. As I said, we built whole products, not just the models, so we needed a way to plug functionality in.
We're actively developing this.
>In any case, I'd like to know more, or to have some information on relevant topics that might be useful to understand and find workarounds for these issues!
Sure, shoot us an email at the site below or using the info in my bio.
[0]: https://iko.ai/docs/notebook/#long-running-notebooks