AI Notebooks - Tutorial - Create your first Machine Learning model

How to build your first Machine Learning model thanks to Miniconda

Last updated 1st September, 2022.

Objective

This tutorial will allow you to create your first OVHcloud AI notebook based on a very simple Machine Learning model: the simple linear regression.

At the end of this tutorial, you will have learned to master OVHcloud AI Notebooks and be able to predict the scores obtained by students as a function of the number of hours worked.

We will be able to predict a student's exam score based on the amount of time he has studied using a dataset available on Kaggle: Students Score Dataset.

Requirements

Instructions

You can launch your notebook from the OVHcloud Control Panel or via the ovhai CLI.

Launching a Jupyter notebook with "Miniconda" via UI

To launch your notebook from the OVHcloud Control Panel, refer to the following steps.

Code editor

Choose the Jupyterlab code editor.

Framework

In this tutorial, the Miniconda framework is used.

With Miniconda, you will be able to set up your environment by installing the Python libraries you need.

You can choose the conda version you want.

The default version of conda is functional for this tutorial.

Resources

You can choose the number of CPUs or GPUs you want.

Here, using 1 CPU is sufficient.

Launching a Jupyter notebook with "Miniconda" via CLI

If you want to launch it with the CLI, choose the jupyterlab editor and the conda framework.

To access the different versions of conda available, run the following command.

ovhai capabilities framework list -o yaml

If you do not specify a version, your notebook starts with the default version of conda.

Choose the number of CPUs (<nb-cpus>) to use in your notebook and use the following command.

ovhai notebook run conda jupyterlab \
    --name <notebook-name> \
    --framework-version <conda-version> \
    --cpu <nb-cpus>

You can then reach your notebook’s URL once the notebook is running.

Accessing the notebook

Once the repository has been cloned, find your notebook by following this path: ai-training-examples > notebooks > getting-started > miniconda > ai-notebooks-introduction > notebook-introduction-linear-regression.ipynb.

A preview of this notebook can be found on GitHub here.

Go further

  • If you want to learn more about the field of Computer vision and Image Classification, check out this notebook.
  • If you are interested in NLP (Natural Language Processing), familiarise yourself with speech to text by following this tutorial.

Feedback

Please send us your questions, feedback and suggestions to improve the service:


Esta documentação foi-lhe útil?

Não hesite em propor-nos sugestões de melhoria para fazer evoluir este manual.

Imagens, conteúdo, estrutura... Não hesite em dizer-nos porquê para evoluirmos em conjunto!

Os seus pedidos de assistência não serão tratados através deste formulário. Para isso, utilize o formulário "Criar um ticket" .

Obrigado. A sua mensagem foi recebida com sucesso.


Estes manuais também podem ser úteis...

OVHcloud Community

Aceda ao seu espaço comunitário. Coloque as suas questões, procure informações e interaja com outros membros do OVHcloud Community.

Discuss with the OVHcloud community

Em conformidade com a alteração à Diretiva 2006/112/CE, os preços com IVA podem variar de acordo com o país de residência do cliente
(por defeito, os preços com IVA apresentados incluem o IVA português em vigor).