| Summary: | Packaging in Python has always been polarizing. From complicated beginnings where you couldn't uninstall libraries, to virtualenv that allows you to work in a self-contained environment that can be thrown away. In this video, I'll present an introduction to Conda, and to a chanel-specific variation of it that is maintained by the community called miniforge. If you are looking for a way to get scientific packages for the new Apple M1 silicon, this video will also help you out get everything sorted, including installing versions of Python that are pre-packaged and ready for data science tasks. Topics include: * Install Conda by using the community version called miniforge. * Use conda to install a specific version of Python, without system installs * Find more about the differences between virtualenv, pip, and conda * Install data science libraries in the new Apple M1 silicon Useful links: * Conda documentation * Conda Forge community documentation * Conda miniforge project
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