Reminds me of https://riverml.xyz/latest/ (which is awesome) but the idea is even better because it skips all the copying and preprocessing yak shaving. Can't wait to kick the tires!
Show HN: PostgresML, now with analytics and project management
51–60 of 76 posts
Re: Show HN: PostgresML, now with analytics and project management
#52I wonder if/how a PostgreSQL plug-in can provide an optimal mix of computing and storage resources for varying machine learning workloads.
Re: Show HN: PostgresML, now with analytics and project management
#53Hello really nice ! Can you explane the differences with https://madlib.apache.org/ ? Wouldnt an OLAP db better suited than pg for this kind of workload ? Does being a postgreSQL module make it compatible with citus, greemplum or timescale ?
OLAP vs OLTP will depend on your ML use case. Online predictions will likely be better served by an OLTP vs offline batch predictions being better served by OLAP. OLAP use cases often involve a lot of extra complexity out of the gate, and something we're targeting is to help startups maintain the simplest possible tech stack early on while they are still growing and exploring PMF. At a high enough level, it should ju…
How about the difference between this and the Madlib project? Better ergonomics?
I've used Madlib in the past and although it was 'successful', the constraint was unfamiliarity with the library from our data scientists, who preferred the classic Python libraries.
Re: Show HN: PostgresML, now with analytics and project management
#54Earlier quoted context omitted.
The data split technique is one of the optional parameters for the call to ‘train’. Model degradation is a really interesting topic, that is hopefully made less difficult when retraining is trivialized, but we also want to add deeper analytics into individual model predictions, as well as better model explanations with tools like shap. We haven’t exposed custom performance metrics in the API yet, but we’re computing…
When I was talking about metrics I meant metrics of the model (accuracy, precission, recall, mean square error, etc), not performance.
We currently calculate those as applicable to classification and regression, but they are only displayed on a model detail page like here:
https://demo.postgresml.org/models/1 https://demo.postgresml.org/models/15
The short term goal would be to expose more metrics from the toolkit.
Re: Show HN: PostgresML, now with analytics and project management
#55Do you plan on adding support for managed PostgreSQL services like RDS in the future?
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Re: Show HN: PostgresML, now with analytics and project management
#56This is great - will be experimenting with one weekend soon...
Re: Show HN: PostgresML, now with analytics and project management
#57I wonder if/how a PostgreSQL plug-in can provide an optimal mix of computing and storage resources for varying machine learning workloads.
Stateful services like Postgres cannot be rapidly scaled up/down to adjust to daily loads, even when those loads are very predictably busy at noon, but often sit idle overnight. Scheduling ML jobs while the db is typically wasting resources might be an efficient strategy.
Re: Show HN: PostgresML, now with analytics and project management
#58Do I need to know about ML/statistics to interpret the results?
Re: Show HN: PostgresML, now with analytics and project management
#59Interesting concept, but I think Big Query ML [1] has been providing similar features for years now. Curious to learn what are the differences, other than offering this as a Postgres plugin.
Re: Show HN: PostgresML, now with analytics and project management
#60Sql to rule the world! Now just Sql to create GUI and websites and I'm