For AI agents: the complete documentation index is available at https://docs.dataplatform.ovh.net/llms.txt, the full documentation bundle is available at https://docs.dataplatform.ovh.net/llms-full.txt, and this page is available as Markdown at https://docs.dataplatform.ovh.net/legacy/getting-started-ml.md.
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    • Build your AI model from scratch on ForePaaS

    Warning

    This tutorial uses the Machine Learning Manager, a service of the ForePaaS Legacy Platform that is not available on OVHcloud Data Platform. See the current tutorials.

    If you’ve been hearing about how Artificial Intelligence (AI) can help you make better business decisions and want to add more intelligence and machine learning to the data you have on hand, you're in the right place!

    In this tutorial, you'll learn the basics about the ForePaas Platform Artificial Intelligence features. You'll create, train and deploy your own AI model in less than 30 minutes.

    ⛳️ The goal is to get you up to speed on how to use the AI features of the ForePaas Platform so that you can start operationalizing AI asap.

    📥 No need to bring your own data or model, we provide them throughout the tutorial to accelerate the process.

    Info

    If you have never used the ForePaaS Platform before, we suggest you have a look at the first 3 parts of our Getting Started guide to learn how your Connectors, Lakehouse Manager and Data Processing Engine work.

    AI in production in five easy steps

    Generally speaking, the creation and deployment of your machine learning model will be completed in 5 major steps:

    1
    Dataset

    Data preparation

    Specify your train and test datasets.

    2
    Training

    Training procedure

    Choose the algorithm at the core of your model.

    3
    Tuning

    Hyper-parameter tuning

    Fine-tune the hyper-parameters of your estimator using our insightful studio.

    4
    Validation

    Model selection

    Compare trained models and pick the one that suits your needs.

    5
    Deployment

    Deployment settings

    Specify the settings for your production-grade inference service

    ?>💡 Good news!
    The Machine Learning Manager, as in the rest of the platform, does a lot of the work for you automatically, from the configuration to the deployment and scalability. This will help you focus on the logic of your AI model rather than the technical administration. ⭐