MLOps 101: Getting Started with ML at Scale
Registration Details

    26th May, 2.00 PM BST / 3.00 PM CEST

    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:

    1. How to pick the right approach for your MLOps solution
    2. How to prioritise the right components (for data validation, continuous training, model monitoring, and more) and tailor your solution to your needs
    3. How to get started on Vertex AI with Datatonic’s open-sourced MLOps Turbo Templates

    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.



    This event is aimed at a technical audience (developers and engineers) who are interested in Vertex AI / Google Cloud Platform.


    2.00 PM BST / 3.00 PM CEST

    Introduction to MLOps + Vertex AI

    Datatonic + Google Cloud
    2.15 PM BST / 3.15 PM CEST

    How to Get Started with Your MLOps Platform & Tailor to Your Business' Needs

    2.30 PM BST / 3.30 PM CEST

    Demo: Launching Datatonic’s Open-Sourced Templates for Vertex AI

    2.45 PM BST / 3.45 PM CEST


    Speakers + Audience


    Tanmaiyii Rao
    ML Specialist, Google Cloud

    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 Curtis
    MLOps Business Lead, Datatonic

    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 Browning
    Principal MLOps Engineer, Datatonic

    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.

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