These are my go-to libraries for Python data crunching.

MotherDuck is launching Flights, an agent-native data pipeline that enables users to choose the MCP server and AI agent of their choice to build and deploy data pipelines in minutes using a flexible, ...

Retrieval-augmented generation enhances the performance of AI agents by expanding their recall. It can do this in three ...

ENVIRONMENT: An Investment company is searching for a talented and driven Data Scientist to join their innovative and growing team based in Durbanville, Cape Town. This is an exciting opportunity to ...

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.

A campaign active since last November has been targeting Python developers building Telegram bots with trojanized Pyrogram ...

Couchbase AI Data Plane combines persistent agent memory, vector search and an enterprise MCP server that runs on-device when ...

Every Python developer knows some or all of these libraries, because they’re stable, reliable, and excellent at what they do.

Spring AI 2.0 advances the Java framework for generative AI apps with a Spring Boot 4 baseline, cleaner agentic tooling, Model Context Protocol support and vendor-backed integrations including Azure ...