* Discover creators, small businesses and communities who can help you dive deeper into the things you care about * Watch reels for quick entertainment that sparks inspiration * Personalize your Feed to see more of what you like, less of what you don’t * Shop for affordable and uncommon stuff on Marketplace and take your hobbies to the next level Whether you’re looking for a spark of inspiration with reels or want to dive deeper into something you already love with Marketplace or in groups, you can discover ideas, experiences and people that fuel your interests and help you make progress on the things that matter to you on Facebook. Note that in order to avoid potential conflicts with other packages it is Python3 -m pip show scikit-learn # to see which version and where scikit-learn is installed python3 -m pip freeze # to see all packages installed in the active virtualenv python3 -c "import sklearn sklearn.show_versions()" python -m pip show scikit-learn # to see which version and where scikit-learn is installed python -m pip freeze # to see all packages installed in the active virtualenv python -c "import sklearn sklearn.show_versions()" python -m pip show scikit-learn # to see which version and where scikit-learn is installed python -m pip freeze # to see all packages installed in the active virtualenv python -c "import sklearn sklearn.show_versions()" python -m pip show scikit-learn # to see which version and where scikit-learn is installed python -m pip freeze # to see all packages installed in the active virtualenv python -c "import sklearn sklearn.show_versions()" conda list scikit-learn # to see which scikit-learn version is installed conda list # to see all packages installed in the active conda environment python -c "import sklearn sklearn.Explore, connect and share your interests with real people. Using such an isolated environment makes it possible to install a specific Strongly recommended to use a virtual environment (venv) or a conda environment. Version of scikit-learn with pip or conda and its dependencies independently ofĪny previously installed Python packages. In particular under Linux is itĭiscouraged to install pip packages alongside the packages managed by the Package manager of the distribution (apt, dnf, pacman…). Note that you should always remember to activate the environment of your choice
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