UbiOps Release Webinar

During the session, Anouk Dutree, Product Owner at UbiOps, gave a demo of several new features, which we have recently added to our platform.
She demonstrated how to deploy R code in UbiOps, set up monitoring emails and more. In case you missed the live session, we got you covered with the recording of the demo.

Webinars, hands-on workshops and podcasts!

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Introduction to MLOps and a model deployment tutorial

In this session, together with Riga Data Science Club, we reviewed important concepts and walk through a hands-on tutorial of an MLOps use case! We showed you how easy it is to deploy your model within 5 minutes on a production-grade (Kubernetes) cluster using UbiOps and make requests to it. 

UbiOps user event: AI ethics, AI audits and detecting deep fakes

On Thursday 11th of February from 14:00 to 16:00, we organized an online UbiOps User Event for customers, partners and our network. It’s invite-only to ensure high-quality discussions take place. The event is set up to inspire and share knowledge on themes that relate to UbiOps, such as AI ethics, AI audit, a deep fake detection use case and the future roadmap of UbiOps. 

Van algoritme tot schaalbare applicatie (in Dutch)

Hosts Jurjen Helmus and Lex Knape talk with our CEO Yannick Maltha about the story of UbiOps and the challenge for many organizations to bring data science projects from proof of concepts to live applications.
If you are working on a data science project and are curious about these challenges and the possibilities, then you should definitely listen to this podcast!

CTO at UbiOps Victor Pereboom gave a talk at the Data Science Salon

From algorithm to scalable application: How to bring data science beyond a proof-of-concept? Victor shared the origin story of UbiOps, and how we solved the challenge of transforming data science algorithms into scalable applications.

Data Science Lifecycle: step-by-step from model development to deployment

Together with Dr. Alexander Friedenberger, Educational Data Scientist at StackFuel, we will take you through the data science lifecycle, step-by-step. From development to deployment of the model. First, we focus on model experimentation using Jupyter notebook. After that, we export the model to UbiOps to deploy it within minutes.

Why is ML deployment important for data scientists?

During the online meeting we discussed the deployment of Machine Learning models, we looked at the goals of deployment technologies but we also familiarized you with game-changing method of implementing artificial intelligence algorithms and tell you why is it so different than conventional software.

AI in Asset Management

This time, we focused on AI in Asset and Property Management, with presentations from ground-breaking companies in the sector. UbiOps presented the client use-case with Asset Rail. Asset Rail wanted to monitor over 500 switches and more than[masked] flips of the Dutch railroads. They used time series data and different models, such as regression models and neural networks, but needed support from UbiOps to monitor and deploy their models quickly and effectively.

Deploying Machine Learning projects at scale with UbiOps by Dutch Analytics and Booking.com

During this webinar, Thomas Cassou, the Director of Machine Learning platform from Booking.com will tell you about some of their applications, the challenges his team faces, and some of the solutions and tradeoffs they have found to leverage machine learning in production.