Machine Learning Images

  • Base Image
    Ubuntu Bionic
  • Compatiiblity
    Cuda® 10, Python 3.7
  • Machine Learning Frameworks
    Scikit-Learn, Nvidia® RAPIDS
  • Deep Learning Frameworks
    Tensorflow, Keras, Pytorch, Fast.ai, JAX
  • Interactive Workspaces
    Jupyter Notebook
  • Containerization
    Docker & Managed Kubernetes Compatible
Prepacked images
Security updates
AI/ML Frameworks
Available region
  • Paris
  • Optimized performance on GPU
  • Maintained by Scaleway
  • Ecosystem integration
Free tool

Ready-to-go Machine Learning Images

Scaleway’s Machine Learning Images provides to Experts of various fields – such as Artificial IntelligenceMachine LearningDeep Learning or BigData and Data Engineers  – the most popular tools for their workflow, quickly and simply.

Every projects can be enhanced using our world-class GPU in the Cloud, with the Frameworks, tools and packages that you need directly on your instances: PyTorch, Tensorflow, Nvidia® RAPIDS, JAX…

Our GPU Machine Learning Images are provided at no additional cost.

 

Ubuntu Bionic ML 10.1
CUDA® 10.1

Ubuntu Bionic ML 10.1 is the last version of Scaleway’s Machine Learning Images. It includes the most recent stable versions of your frameworks: CUDA 10.1, Tensorflow 2.2, PyTorch 1.5.

Deploy this ML image
Ubuntu Bionic ML 9.2
CUDA® 9.2

Ubuntu Bionic ML 9.2 is a Scaleway Machine Learning image specially maintained for the users that needs an anterior version based on CUDA 9.2

Deploy this ML image

What's inside our Machine Learning Images

Every Framework and packages prepacked

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Tips: You can have a full detailed list of the Python packages and versions pre-installed in the conda “ai” environment by looking at the content of the /root/conda-ai-env-requirements.frozen file in the ML images

All the most popular Machine and Deep Learning tools are here

TensorFlow & Keras

TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.
Keras is now the default high-level API in Tensorflow 2.0

PyTorch

Pytorch is an open source machine learning framework that accelerates the path from research prototyping to production deployment. PyTorch enables fast, flexible experimentation and efficient production through a user-friendly front-end, distributed training, and ecosystem of tools and libraries.

scikit

Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

RAPIDS

The RAPIDS data science framework is a collection of libraries for running end-to-end data science pipelines completely on the GPU. The interaction is designed to have a familiar look and feel to working in Python, but utilizes optimized NVIDIA® CUDA® primitives and high-bandwidth GPU memory under the hood.

Conda

Conda is an open-source package management system and environment management system for Linux. Conda quickly installs, runs, and updates packages and their dependencies.
With just a few commands, you can set up a totally separate environment to run that different version of Python, while continuing to run your usual version of Python in your normal environment.

And many more

A lot of other tools, framework and librairies are packed in our Machine Learning images, such as Natural Language Processing tools (spacybeautifulsoup4), Visualization tools (matplotlibbokehseabornplotly) , images manipulation (NVIDIA® DaliPillow),  implementation of Gradient Boosting algorithmes (XGBoostCatBoost) or for Forecasting (Facebook Prophet).

Try now with our tutorials dedicated to AI

Introducing GPU Instances: Using Deep Learning to Obtain Frontal Rendering of Facial Images

Read the article

Boost your Machine Learning with Scaleway

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