With MindsDB and MariaDB, businesses can quickly and automatically produce models that analyze any data, no matter its complexity or type, and deliver faster, more accurate results – even on a very large scale.

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Combining both MindsDB and QuestDB gives you unbound prediction ability with SQL

In this blog post you’ll see how to deploy a natural language processing ML model written in Keras into a database and call it via SQL …

This article shows why and how a new data-centric construct called AI Tables makes self-service ML easy for data engineers, developers, and business analysts.

It’s almost a given that the brightest tools in machine learning are written for Python. However, those with the deepest understanding of company data often speak SQL. Imagine what they could do if machine learning was at their fingertips—not in a Python environment but in the data layer—where they’re most effective. …

In this article, we will be reviewing how we can integrate predictive capabilities powered by machine learning with the ClickHouse database.

The predictions machine learning and AI provide to your organization can only drive business outcomes if decision makers are willing and able to rely on those predictions. This blog will discuss the role of explainability in machine learning to help decision makers feel more confident in ML models by fully understanding how predictions are generated.

A scientific method for machine learning and the advantage to bringing machine learning models to the "mountains" of data.

What level of confidence do you have in your machine learning predictions. The first step in improving ML predictions is determining how reliable those predictions are. This blog will discuss the value of Explainable AI and provide tips to improve ML predictions.