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Conda is like pip, except that it also manages shared library dependencies, including providing prebuilts.
This has made Conda very popular in the deep learning community around 2020, where using Python frontends like PyTorch to configure faster precompiled backends was extremely common.
It also means that it is a full package manager and extremely overbloated and blows up all the time. People should just use Docker instead for that kind of stuff: www.reddit.com/r/learnmachinelearning/comments/kd88p8/comment/keco07k/
You also have to buy a license to use their repos if you are part of a large-enough organization: stackoverflow.com/questions/74762863/are-conda-miniconda-and-anaconda-free-to-use-and-open-source

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