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You are correct. Our technical documentation is mostly aimed at working scientists who want to start using these techniques in their work. That does sometimes l
by KenoFischer 6y ago
You are correct. Our technical documentation is mostly aimed at working scientists who want to start using these techniques in their work. That does sometimes lead to funny cases where a document assumes you know what a smooth manifold is but will explain try/catch blocks. We've started trying to put together more introductory-focused material at https://juliaacademy.com/ https://juliaacademy.com/. We don't currently have anything particularly AD focused (outside of the general ML courses), but I think that's a topic that's high on the interest list.
- dgb23 6y agoThank you for pointing out this fantastic resource. > mostly aimed at working scientists My primary goals are to learn what (primarily) data-scientists do. In the sense of: How do they think and approach problems, what are the limitations and the prerequisites etc. (And as I said to improve my math skills.) I think there is merit in engineers learning these things (within reasonable scope) because at some point there needs to be a system that provides and transforms data into a format that scientists/analysts can work with. And in the other hand there are things that engineers can implement and learn to improve their systems. I'm excited about both and curious about how far I can get.