Snowflake + Snowpark Python = machine learning?

This page summarizes the projects mentioned and recommended in the original post on dev.to

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  • pip

    The Python package installer

  • "Vendorized package" basically means copying all the files locally and treating them as part of your current project. If you choose to vendor a dependency, you should follow the pip guidelines. In fact, since you need pip to install packages, pip itself comes with some vendorized packages.

  • snowflake-ml

    Toy use case on how to use Snowflake as a full ML platform.

  • If you made this far, thanks for reading! I'll discuss the actual solution on a next post! I'll also throw in a bit of Confluent Cloud, Terraform Github Actions and Streamlit. If you're impatient, feel free to take a peek at the project repo! I'll see you next time! 🚀

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    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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  • Pytorch

    Tensors and Dynamic neural networks in Python with strong GPU acceleration

  • Dependencies. The dependencies is a subset of conda dependencies. By conda I mean the same Anaconda that you may know as a package index or for your virtual environments. The dependencies are not always the latest sometimes. It also means that other pip packages that are not available in conda are not easily available. You may still be able to include vendorized packages in your project to bypass this restriction. Package names occasionally differ from pip and conda (for example, PyTorch is installable as torch in pip, but pytorch in conda).

  • Poetry

    Python packaging and dependency management made easy

  • Package wheels are the .whl files that are uploaded to pip to distribute packages. If you are familiar with Poetry, poetry build actually builds the wheels that are used before publishing with poetry publish.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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