This site uses cookies. By continuing to browse, you agree to our use of cookies as outlined in our Privacy and Cookie Policy.
Join Datatonic and Google Cloud for practical tips on designing and building your MLOps capability using Vertex AI, and find out:
+ How to pick the right approach for your MLOps solution
+ How to prioritise the right components (for data validation, continuous training, model monitoring, and more) and tailor your solution to your needs
+ How to get started with Datatonic’s open-sourced MLOps Turbo Templates
A year since its release, Google’s Vertex AI has not only been named a leader in AI Infrastructure (Forrester, 2021) but has also consistently added new capabilities to help teams accelerate ML models with MLOps.
But, getting started with a full-scale MLOps solution can be a challenge. With tooling, budget, and team capacity & capability to consider, how do you know where to begin?
Join Datatonic and Google Cloud for practical tips on designing and building your MLOps Platform using Vertex AI, and find out:
In this webinar, Datatonic will launch MLOps Turbo Templates – an open-sourced code co-developed with Google that provides much of the boilerplate for an MLOps solution, including CI/CD, Infrastructure as Code, example ML pipelines using Vertex Pipelines, development / helper scripts.
Audience
This event is aimed at a technical audience (developers and engineers) who are interested in Vertex AI / Google Cloud Platform.
Introduction to MLOps + Vertex AI
How to Get Started with Your MLOps Platform & Tailor to Your Business' Needs
Demo: Launching Datatonic’s Open-Sourced Templates for Vertex AI
Q&A
Tanmaiyii is an ML Specialist for Digital Natives at Google Cloud, advising and enabling customers to derive value using ML. Before joining Google, Tanmaiyii has worked as a management consultant specialising in Data Analytics/Data Science. She also holds a Master’s degree in Data Science from Queen Mary University and has collaborated with a MedTech startup for her Master’s Thesis.
Jamie works to develop Datatonic's commercial strategy for MLOps solutions, and has enabled successful project delivery for industry-leading clients (e.g. Sky). Jamie holds a 1st class degree in Chemical Engineering from Imperial College London, and comes from a management consulting background.
Jonny has led the development and project delivery for Datatonic's open-source MLOps templates, and continues to drive & implement their technical direction through a combined skillset of DevOps and ML Engineering disciplines. Jonny holds a 1st class degree in Computer Science from Durham, and has previously been a specialist in technical theatre & AV.
Know exactly where and how to start your AI journey with Datatonic’s
three-week AI Innovation Jumpstart *.
* Duration dependent on data complexity and use case chosen for POC model
With your own data sets, convince your business of the value of migrating your data warehouse, data lake and/or streaming platform to the cloud in four weeks.
With your own data, see how Looker can modernise your BI needs
with Datatonic’s two-week Showcase.