AI/ML

GPT4All is an open source tool that lets you deploy large language models locally without a GPU. Learn how to integrate GPT4All into a Quarkus application.

This article explores leveraging AI to generate Apache Camel routes using ChatGPT.

Get up and running with Ansible Lightspeed, a new generative AI service for Ansible automation, and the Ansible VS Code extension by Red Hat.

Discover the power of AI/ML in software testing with Bunsen, a Python-based toolkit that lets you analyze and report test-suite logs using an SQLite database.

Join Ian 'Uther' Lawson for a fun overview of what AI/ML actually is today, how containerized technologies are a godsend for developers, and where the industry might go next.

Walk through the basics of fine-tuning a large language model using Red Hat OpenShift Data Science and HuggingFace Transformers.

Learn how to use the Red Hat OpenShift Data Science platform and Starburst to develop a fraud detection workflow with an AI/ML use case.

In this session, Avishay Sebban will give an overview of the challenges of running distributed workloads for machine learning.

Learn why graphics processing units (GPUs) have become the foundation of artificial intelligence and how they are being used.

In this article, you will learn how to perform inference on JPEG images using the gRPC API in OpenVINO Model Server in OpenShift. Model servers play an important role in smoothly bringing models from development to production. Models are served via network endpoints which expose an APIs to run predictions.

Intel AI tools save cloud costs, date scientists' time, and time spent developing models. Learn how the AI Kit can help you.

Online events and regional events held around the world with Red Hat's Developer Advocates.

OpenVINO helps you tackle speech-to-text conversion, a common AI use case. Learn more.

You can perform edge detection on images using this Jupyter notebook on any Kubernetes cluster. Learn how.

Create an open source machine learning environment quickly with Pachyderm, JupyterHub, and Ceph Nano on Open Data Hub.

CodeReady Containers lets you easily deploy a virtual cluster environment on your local system, with open source AI tools from Open Data Hub.

Once you have data, how do you start building a PyTorch model? This learning path shows you how to create a PyTorch model with OpenShift Data Science.

OpenShift AI gives data scientists and developers a powerful AI/ML platform for building AI-enabled applications. Data scientists and developers can collaborate to move from experiment to production in a consistent environment quickly.

Streaming data is key to many modern applications. This tutorial walks you through setting up a data stream using Amazon Kinesis and Node.js.

Don't miss a thing! Here's a roundup of new articles, tutorials, and more published this month on Red Hat Developer.

Learn how to set up a Pulp Python repository and publish and consume Python packages using Pulp on the Red Hat Developer Operate First cloud.

Discover how to resolve Python dependencies by extracting metadata and dependency information, and how Project Thoth helps to streamline the process.

Solve the typical data science problems of accessing Amazon S3 data and creating a TensorFlow model by following two new OpenShift Data Science learning paths.

Learn how to better build and extend containerized apps by using Project Thoth to control container image quality and provide more robust runtime environments.