Data Science

AI Red Hat

OpenShift AI helps you set up an MLOps “conveyer belt”

Many developers struggle with putting a model into deployment. The difficulty of updating models in production often leads to hesitancy and delays. The concept of MLOps deals with putting models into production without it being painful or risky. With Red Hat OpenShift AI, data scientists can create models with their preferred tooling, create pipelines to […]

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AI Red Hat

OpenShift AI as a foundation

Red Hat’s AI platform enables the development and deployment of models across the public cloud, data center, and edge. It manages cluster resource requests, such as scaling up and down GPUs, and fosters collaboration between developers and data scientists. All by expanding the DevOps tooling provided within OpenShift, providing additional capabilities such as model serving […]

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Azure Big Data Data Data Warehouse Microsoft

Your data is in the Lakehouse, but now what? | Microsoft Fabric (Public Preview)

This video is from Guy in a Cube. You’ve got your data into OneLake and a Lakehouse, but now what? What can you do with that data after you’ve landed it in Microsoft Fabric? Justyna walks us through different areas where you can leverage your data throughout fabric. From data warehouses to even Power BI!

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AI Open Source Red Hat

A collaborative platform with OpenShift AI

Red Hat OpenShift AI provides a secure, reliable and consistent platform across the hybrid cloud.  Data scientists, MLOps engineers, and application developers can work together on the same cloud-native platform, leading to faster business insights with trusted outcomes. Providing innovative AI/ML tooling from the open source world but with the support and security of Red […]

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Data Science

Stanford’s FREE data science book and course are the best yet

This video from Python Programmer explores Stanford’s free data science book and course.

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Data Python

Data Engineering 101: How to Build a real world dataset end-to-end: Part II

This video is from Deep Data Science. Data Engineering is a fundamental yet neglected skill by many data scientists. In this series I’m going to show step-by-step how I construct real world dataset for machine learning (e.g. FlowDB 2.0) from a variety of sources. I will also describe differences between this dataset and constructing data-lakes […]

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AI Red Hat

Data science pipelines on OpenShift

Guillaume Moutier describes the new data science pipelines capability within Red Hat OpenShift Data Science that allows data scientists, data engineers and app developers to ingest data and clean it within the Jupyter environment, and then deploy as an OpenShift pipeline. Data practitioners can automate the full cycle within and intuitive drag-and-drop UI. Check out […]

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AI Generative AI Red Hat

Unlock the Power of Generative AI with the Right Platform Stack

Taneem Ibrahim and Selbi Nuyryev describe the work in the Open Data Hub community about building an AI/ML stack for generative AI and foundation models. With project CodeFlare and open source technology work with CAIkit, KubeRay and Text Generation Inference Service (TGiS), KServe to prompt-tune pre-trained models and provide resource efficiency across the hybrid cloud. […]

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AI Generative AI Red Hat

Get the Scoop on OpenShift AI from Red Hat’s Chris Wright

Chris Wright, Red Hat CTO, describes Red Hat OpenShift AI and how it extends Red Hat’s application platform to help data scientists and developers collaborate to bring ai-enabled applications into the enterprise. Leveraging DevOps principles, OpenShift AI works across the entire model development lifecycle to help AI/ML teams build, deploy and monitor models across the […]

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