PostgresML

PostgresML: Complete MLops Platform in PostgreSQL Extension

PostgresML is a complete MLops platform in a simple PostgreSQL extension. Build fast, simple and powerful models right inside your database.

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What is PostgresML?

PostgresML is a complete MLops platform in a simple PostgreSQL extension. Build fast, simple and powerful models right inside your database.

How to use PostgresML?

It's simple to use PostgresML. Just follow these three steps: 1. Train your model using the pgml.train() function. 2. Deploy your model using the pgml.deploy() function. 3. Make predictions using the pgml.predict() function.

PostgresML's Core Features

Seamless in-database MLops platform

High efficiency with minimal latency and computational cost

Open-source platform with various ML libraries

Instant scalability with custom Postgres pooler

Work with popular toolkits and models

PostgresML's Use Cases

smart_toy Chatbots

manage_search Site Search

e911_emergency Fraud Detection

avg_pace Forecasting

FAQ from PostgresML

What is PostgresML?

PostgresML is a complete MLops platform in a simple PostgreSQL extension. Build fast, simple and powerful models right inside your database.

How to use PostgresML?

It's simple to use PostgresML. Just follow these three steps: 1. Train your model using the pgml.train() function. 2. Deploy your model using the pgml.deploy() function. 3. Make predictions using the pgml.predict() function.

How can I use PostgresML?

Using PostgresML is easy. Just follow the three steps: train your model, deploy it, and make predictions. You can use functions like pgml.train(), pgml.deploy(), and pgml.predict() to perform these tasks.

What are the core features of PostgresML?

PostgresML offers features like seamless in-database MLops platform, high efficiency with minimal latency and computational cost, open-source platform with various ML libraries, instant scalability with custom Postgres pooler, and the ability to work with popular toolkits and models.

What are the use cases of PostgresML?

Some common use cases of PostgresML include building smart_toy Chatbots, managing site search, detecting fraud in e911_emergency situations, and performing time series forecasting with avg_pace.

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