superlinked meets next-gen career profiles #95
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Hi @gitNetw0rk I'm one of the founders & I'm very happy to answer any question you have regarding Superlinked! We already have one team working on a superlinked-powered infrastructure in the jobs/talent marketplace vertical, so you are in a good company! In the meantime, check out docs.superlinked.com - especially the concepts for practical python notebook-based examples of how you can use the different features of the framework. |
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thanks @svonava ! I am studying the concepts, I guess it needs more time :) |
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Sure thing, keep us posted! Another useful resource are end-to-end app recipes - we don't have one for jobs search/recommendations yet, but here is one for hotel search: |
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Any updates on this @gitNetw0rk ? |
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Hi @svonava, I am working on it and thank your for asking! I am still mostly occupied with web dev, my search pipeline will follow soon.. Meanwhile I tried out all your public notebooks, as you suggested, which helped me understand all concepts well enough. I have one architectural critical question open, I am curious if you could provide some thoughts on best practice. Assuming Qdrant as container service, while having app with occasional need to write to target collections as well, it is a recommended approach to have one collection-per-model-per-user, in order to optimize search performance? I have not found any info on how to approach this with Superlinked framework in mind. I am curious if this makes sense to try to implement or me just over-engineering. Thanks! |
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Hi guys,
I am supercurious If I can meet here somebody technical to consult superlinked implementation cons and pros for my product.
Superlinked seems fit for my case, yet I still have hard time to wrap my head around it and/or figure out how to tackle data modelling and processing requirements, at the high level, in my case smartly.
Meanwhile I am testing a prototype version of my app. In short, it helps people create and maintain individual career profiles. Seen technically, it its core, it extracts, indexes and retrieves information. It also implements quality assurance measures, constrains and features required to provide users' with resumes/CVs of certain quality.
I am planning new stack, which will enable me to operationalize the whole model I have in mind. There are challenges when it comes to representing professional experience and aspirations in digital, in the first place. Besides, there are further challenges to interpret that data by somebody else accurately...
Anyways, if you like the topic and like to help me move on, lets get in touch and schedule up for details. Thanks!
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