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Blog Functionality Product update
April 19, 2023 / July 26, 2023 by [email protected]
UbiOps release news – version 2.23.0 On the 20th of April 2023 we have released new functionality and made improvements to our UbiOps SaaS product. An overview of the changes is given below. Python client library version for this release: 3.15.0 CLI version for this release: 2.15.0 ✔️Support for Training (Beta) We added new functionality […]
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Functionality Product update UbiOps
January 10, 2023 / July 26, 2023 by [email protected]
UbiOps release news – version 2.21.0 On the 10th of January 2023 we have released new functionality and made improvements to our UbiOps SaaS product. On this page you can read all about it. We have also prepared a release demo for you! Create your free account ✔️ New file system To improve working with files […]
Blog Functionality Product update Technology UbiOps
March 17, 2022 / July 26, 2023 by [email protected]
UbiOps version 2.15.0 On the 17th of March 2022, we have released new functionality and made improvements to the UbiOps SaaS product. Here is an overview of the new functionality and changes: Create your free account On-demand GPUs We already provided GPU support but we expanded this functionality to be on-demand. That means that […]
Blog Collaborations
June 7, 2021 / January 5, 2024 by [email protected]
UbiOps and Arize UbiOps is the easy-to-use serving and hosting layer for data science code. UbiOps stands out for its ease of use, freedom to write any code you want while eliminating the need for in-depth IT knowledge. It is a serving, hosting and management layer on top of your preferred infrastructure. Accessible via the […]
Blog Product update
June 3, 2021 / July 26, 2023 by [email protected]
On June 3, 2021 we have released new functionality and made improvements to our UbiOps SaaS. Here is an overview of all new functionality and changes in UbiOps: ✔️ Store & query request data It is now possible to store all your requests (batch and direct) in UbiOps. It is configurable on deployment version level […]
Events Product update UbiOps Webinars
April 29, 2021 / July 26, 2023 by [email protected]
UbiOps Release update 2.8.0. The first UbiOps release update shows you in under 30 minutes what changes we have made to the platform in the past month. Curious to follow along, or just sit back and listen to what’s new and how it works? It’s open for anyone, so sign up here and we’ll see you on […]
On the 29th of April 2021 we have released new functionality and made improvements to our UbiOps SaaS. Here is an overview of all new functionality and changes in UbiOps: R language support This release, we proudly present support for R (version 4.0) deployments. The R deployments can be created in the same way […]
April 1, 2021 / July 26, 2023 by [email protected]
UbiOps 2.7.0 is here! On the 1st of April 2021 we have released new functionality and made improvements to our UbiOps SaaS. Here is an overview of all new functionality and changes in UbiOps: Default versions The more versions a deployment has, the harder it is to track which version is the production or […]
Blog Pricing Security
October 14, 2020 / January 5, 2024 by [email protected]
As the field of cloud computing is expanding, we see that many of our clients wonder whether migrating to the cloud is a feasible option for them. It can be hard to keep up with all that is happening when new services and vendors go online every day. We believe that the key to acknowledging […]
Blog
July 30, 2020 / July 26, 2023 by [email protected]
On the 30th of July 2020, we have released a new version (v2.1) of the UbiOps platform. We made major improvements to the underlying architecture over the past months. These result in better performance, faster response times and higher reliability of UbiOps. Besides this, new functionality is available. Check the new Features & Functionality overview […]
June 24, 2020 / July 26, 2023 by support
Are you or any of your colleagues Data Scientists? Have you been involved in bringing data science models in production? Have you seen that the actual machine learning code is only a tiny fraction of the whole solution?
