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Blog posts tagged
"AI/ML"

Andreea Munteanu
4 October 2022

Kubeflow 1.6 on Kubernetes 1.23 and beyond

AI Article

Kubeflow is an open-source MLOps platform that runs on top of Kubernetes. Kubeflow 1.6 was released September 7 2022 with Canonical’s official distribution, Charmed Kubeflow, following shortly after. It came with support for Kubernetes 1.22. However, the MLOps landscape evolves quickly and so does Charmed Kubeflow.  As of today, Canonical ...

Andreea Munteanu
16 September 2022

FAQ: MLOps with Charmed Kubeflow

AI Article

Charmed Kubeflow is Canonical’s Kubeflow distribution and MLOps platform. The latest release shipped on 8 September. Our engineering team hosted a couple of livestreams to answer the questions from the community: a beta-release webcast and a technical deep-dive. In case you missed them, you can read the most frequently asked questions (FA ...

Andreea Munteanu
13 September 2022

Charmed Kubeflow 1.6: what’s new?

AI Article

Kubeflow 1.6 was released on September 7, and Charmed Kubeflow 1.6 (Canonical’s distribution) came shortly after, as it follows the same roadmap. Charmed Kubeflow introduces a new version of Kubeflow pipelines as well as model training enhancements.  Read our official press release. Kubeflow pipelines: a better user experience Kubeflow pi ...

Canonical
8 September 2022

Charmed Kubeflow 1.6 is now available from Canonical

AI Article

The latest release of Canonical’s end-to-end MLOps platform brings advanced AI/ML training capabilities 8 September 2022- Canonical, the publisher of Ubuntu, announces today the release of Charmed Kubeflow 1.6,  an end-to-end MLOps platform with optimised complex model training capabilities.  Charmed Kubeflow is Canonical’s enterprise-rea ...

Andreea Munteanu
17 August 2022

Charmed Kubeflow 1.6 Beta is out: try it today!

AI Article

We are happy to announce that Charmed Kubeflow 1.6 is now available in Beta. Kubeflow has evolved into an end-to-end MLOps platform for optimised complex model training. We’re looking for data scientists, ML engineers and developers to take the Beta release for a drive and share their feedback! Read on to learn more. Read more ...

Michael Iatrou
26 July 2022

Omnichannel Enablement: 4 technology success factors

Cloud and server Article

For retailers considering a transition to omnichannel, there are four key success factors to keep in mind. ...

Bartłomiej Poniecki-Klotz
13 April 2022

MLOps Pipeline with MLFlow, Seldon Core and Kubeflow

AI Article

MLOps pipelines are a set of steps that automate the process of creating and maintaining AI/ML models. In other words, Data Scientists create multiple notebooks while building their experiments, and naturally the next step is a transition from experiments to production-ready code. The best way to do this is to build an effective MLOps pip ...

Maciej Mazur
10 December 2021

WSL for data scientist

AI Article

Windows Subsystem for Linux for data scientists Ubuntu is the number one choice for data scientists worldwide. It is also by far the most popular Linux distribution used on public clouds with machine learning offerings. However, we don’t forget about our Windows friends – many of whom had their operating system chosen by corporate IT ...

Tytus Kurek
14 October 2021

Ubuntu Server 21.10: What’s new?

Cloud and server Article

Ubuntu Server 21.10 (Impish Indri) expands on edge use cases with a minimised system installation option in the Ubuntu Server Live Installer, and native, certified drivers for NVIDIA vGPU software on Ubuntu 20.04 LTS and 18.04 LTS, fully supporting sophisticated AI/ML workloads. ...

aymen frikha
28 July 2021

From notebooks to pipelines with Kubeflow KALE

AI Article

What is Kubeflow? Kubeflow is the open-source machine learning toolkit on top of Kubernetes. Kubeflow translates steps in your data science workflow into Kubernetes jobs, providing the cloud-native interface for your ML libraries, frameworks, pipelines and notebooks. Read more about Kubeflow Notebooks in Kubeflow Within the Kubeflow dashb ...

Rui Vasconcelos
17 May 2021

A guide to ML model serving

AI Article

TL;DR: How you deploy models into production is what separates an academic exercise from an investment in ML that is value-generating for your business. At scale, this becomes painfully complex. This guide walks you through industry best practices and methods, concluding with a practical tool, KFServing, that tackles model serving at scal ...

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