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As no-one's answered this, I'll try though my area is DBs but certainly not ML. AFAIK ML doesn't really care about the source of data so DB is irrelevant. The
by tempguy9999 7y ago
As no-one's answered this, I'll try though my area is DBs but certainly not ML.
AFAIK ML doesn't really care about the source of data so DB is irrelevant. The conjunction of DB and ML in your question makes me wonder if you're sort of confusing the two. AFAIK they are totally independent, though some DBs come with some data mining tools, which is ML eg. MSSQL (you can prob download an eval version for nothing. It's time limited though, 6 months or so).
But to repeat AFAIK ML and DBs are entirely different things.
If you want to grab a DB, well I've no experience with postgres but I've heard a lot that's good, so perhaps start here.
- p1esk 7y agoSo far I’ve been using Excel and Pandas to maintain/pipeline my data, but I feel like a database might be a better way. I’m not sure about built in data mining tools, as I’m used to writing them myself. Also, most of my pipeline configs are in json format so I’ve been thinking about MongoDB.
- tempguy9999 7y agoSounds like you know ML then. Anything non-trivial on a spreadsheet is usually best ported to a DB, that's a pretty good rule of thumb. I don't understand about your configs being in json, nor why that makes it more suitable for mongo. If you need to store semistructured blobs of data, relational DBs can do that fine (in BLOB fields), but IIRC postgres supports json, including indexing into individual json subfields. <http://www.postgresqltutorial.com/postgresql-json/> http://www.postgresqltutorial.com/postgresql-json/> but to repeat, I've never used postgres so speak to someone else first who has. If you can do ML as it seems you are, install postgres and just get started on this tutorial stuff here - best of luck!