Python

Explore the complete machine learning operations (MLOps) pipeline utilizing Red

Discover how you can use the Podman AI Lab extension for Podman Desktop to work

Jupyter Notebook works with OpenShift AI to interactively classify images. In

Explore how the new pyproject RPM macros simplify packaging modern Python projects by supporting diverse build backends and reusing upstream metadata.

Explore how Red Hat Developer Hub and OpenShift AI work together with OpenShift to build workbenches and accelerate AI/ML development.

Discover how Red Hat Enterprise Linux (RHEL) provides security-compliant Python streams with long life cycles.

Cloud native technologies to develop, deploy, and manage responsive and scalable applications anywhere.

Learn how to build a ModelCar container image and deploy it with OpenShift AI.

Learn how to effectively manage Python content for producing Ansible execution environments.

The RamaLama project simplifies AI model management for developers by using OCI containers to automatically configure and run AI models.

This article details new Python performance optimizations in RHEL 9.5.

Find out what's new in Red Hat Enterprise Linux (RHEL) 9.5, including enhancements for workloads, container management and security, and Identity Management.

If you're a Python developer who relies on the Eventlet library, it's time to think about migrating your projects to Asyncio. This article helps you get started.

Red Hat® OpenShift® is a trusted, comprehensive, and consistent platform to develop, modernize, and deploy applications at scale, including today’s AI-enabled apps. Innovate faster with a complete set of services for bringing apps to market on your choice of infrastructure.

This short guide explains how to choose a GPU framework and library (e.g., CUDA vs. OpenCL), as well as how to design accurate benchmarks.

Learn how to write a GPU-accelerated quicksort procedure using the algorithm for prefix sum/scan and explore other GPU algorithms, such as Reduce and Game of Life.

Red Hat OpenShift AI provides tools across the full lifecycle of AI/ML experiments and models for data scientists and developers of intelligent applications.

Train and deploy an AI model using OpenShift AI, then integrate it into an application running on OpenShift.

BERT, which stands for Bidirectional Encoder Representations from Transformers

Event-driven Sentiment Analysis using Kafka, Knative and AI/ML

A practical example to deploy machine learning model using data science...

Red Hat Enterprise Linux (RHEL) 9.4 is now generally available (GA). Learn about the latest enhancements that improve the developer experience.

Learn how to create a Red Hat OpenShift AI environment, then walk through data labeling and information extraction using the Snorkel open source Python library.