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    • This material is an introduction to machin learning with Python. Topics are: Unsupervised Learning: dimensionality reductiong; unsupervised Learning: clustering; supervised Learning: basic methods; supervised Learning: using real data and preprocessing1
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84 materials found
  • course

    Building Better Scientific Software in Python

    programming language python packaging testing documentation logging performance
  • course

    Software Carpentry: R for Reproducible Scientific Analysis

    programming language R reproducibility
  • course

    Software Carpentry: Programming with R

    programming language R
  • course

    Five recommendations for FAIR software, by the Netherlands eScience Center and DANS

    fair version control license registry repository citation checklist
  • course

    A self-assessment checklist for FAIR research software

    fair self-assessment checklist research software
  • course

    Open source definition, by the Open Source Initiative

    open source code license software
  • course

    CodeRefinery: Reproducible research - preparing code to be usable by you and others in the future

    readable code organise software project reproducible environment
  • course

    Top 10 FAIR Data & Software Things

    fair data research software engineers
  • course

    The FAIR Cookbook, online recipes for life scientists that help make and keep data FAIR

    fair life sciences infrastructure assessment
  • course

    10 easy things to make your research software FAIR

    fair software
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This project has received funding from the European Union’s Horizon Europe Programme under GA 101129744 — EVERSE — HORIZON-INFRA-2023-EOSC-01-02