Creating pipelinesįinding patterns in data often proceeds in a chain of data-processing steps, e.g., feature selection, normalization, and classification.
To check that you have scikit-learn, execute in shell: python -c 'import sklearn print(sklearn._version_)'Ĭanopy and Anaconda both ship a recent version of scikit-learn, in addition to a large set of scientific python library for Windows, Mac OSX (also relevant for Linux). However for linux systems it is recommended to use conda package manager to avoid possible build processes conda install scikit-learn The current stable version of scikit-learn requires:įor most installation pip python package manager can install python and all of its dependencies: pip install scikit-learn Scikit-learncontains a number of implementation for different popular algorithms of machine learning. It is based on other python libraries: NumPy, SciPy, and matplotlib Scikit-learn is a general-purpose open-source library for data analysis written in python.
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