# Configure a pipeline

!> This page describes the **Machine Learning Manager**, a service of the ForePaaS Legacy Platform that is not available on OVHcloud Data Platform. See [the current documentation](/en/product/index).

Each pipeline can be configured from the data input to the deployment options in order to create accurate production-grade prediction models. 

![machinelearning](picts/pipeline-main-page-zoomed.png)

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## The five configuration steps

There are five core steps to setting up a pipeline on ForePaaS.


<div class="Project-step">
   <div class="step">1</div>
   <a class="landing-link" href="#/en/product/ml/pipelines/configure/dataset/index.md">
      <img data-no-zoom src="en/product/ml/picts/dataset-icon.png" alt="Dataset" style="width:100px;height:auto;"/>
      <div class="text">
         <h2>Dataset preparation</h2>
         <p>Specify everything related to the train and test datasets of your model.</p>
      </div>
   </a>
</div>
<div class="Project-step">
   <div class="step">2</div>
   <a class="landing-link" href="#/en/product/ml/pipelines/configure/training/index.md">
      <img data-no-zoom src="en/product/ml/picts/training-icon.png" alt="Training" style="width:100px;height:auto;"/>
      <div class="text">
         <h2>Training procedure</h2>
         <p>Set up the estimator at the basis of your model as well as the scoring and validation options needed to fine-tune it.</p>
      </div>
   </a>
</div>
<div class="Project-step">
   <div class="step">3</div>
   <a class="landing-link" href="#/en/product/ml/pipelines/configure/tuning/index.md">
      <img data-no-zoom src="en/product/ml/picts/tuning-icon.png" alt="Tuning" style="width:100px;height:auto;"/>
      <div class="text">
         <h2>Hyper-parameter tuning</h2>
         <p>Fine-tune the hyper-parameters of your estimator using our intuitive and insightful studio.</p>
      </div>
   </a>
</div>
<div class="Project-step">
   <div class="step">4</div>
   <a class="landing-link" href="#/en/product/ml/pipelines/configure/validation/index.md">
      <img data-no-zoom src="en/product/ml/picts/validation-icon.png" alt="Validation" style="width:100px;height:auto;"/>
      <div class="text">
         <h2>Model selection</h2>
         <p>Compare models that have been trained since the creation of your pipeline and decide which to deploy.</p>
      </div>
   </a>
</div>
<div class="Project-step">
   <div class="step">5</div>
   <a class="landing-link" href="#/en/product/ml/pipelines/configure/deployment/index.md">
      <img data-no-zoom src="en/product/ml/picts/deployment-icon.png" alt="Deployment" style="width:100px;height:auto;"/>
      <div class="text">
         <h2>Deployment settings</h2>
         <p>Specify the various settings for your production-grade inference service</p>
      </div>
   </a>
</div>

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## Manage execution options

Once a pipeline is set up, you can manage various execution options to ensure a reliable life-cycle of your models in a production environment. Learn more about the execution of a pipeline and the life-cycle of a model below:

{Manage a pipeline's execution}(#/en/product/ml/pipelines/execute/index.md)

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##  Need help? 🆘

> You didn't find what you were looking for on this page? You can ask for help via the [OVHcloud Help Centre](https://help.ovhcloud.com/csm/fr-home?id=csm_index) or the [support guide](/en/support/index).

{Send your questions to support 🤔}(https://help.ovhcloud.com/csm/fr-home?id=csm_index)