Code & Data for Introduction to Machine Learning with Scikit-Learn
See the full installation instructions for more details; these are provided for convenience only.
Scikit-Learn requires:
- Python >= 2.6 or >= 3.3
- Numpy >= 1.6.1
- SciPy >= 0.9
Once you have installed pip
(the python package manager):
This should be super easy:
pip install -U numpy scipy scikit-learn
Now just wait! Also, you have no excuse not to do this in a virtualenv.
Install numpy and scipy with their official installers. You can then use PyPi to install scikit-learn:
pip install -U scikit-learn
If you're having trouble, consider one of the unofficial windows installers or anacondas (see the Scikit-Learn page for more).
Unfortunately there are no official binary packages for Linux. First install the build dependencies:
sudo apt-get install build-essential python-dev python-setuptools \
python-numpy python-scipy \
libatlas-dev libatlas3gf-base
Then you can build (hopefully) Scikit-learn with pip:
pip install --user --install-option="--prefix=" -U scikit-learn
Keep in mind however, that there are other dependencies and might be issues with ATLAS and BLAS - see the official installation for more.