Lately, I worked through Google‘s fantastic machine learning tutorial by Josh Gordon that you can find here. On a windows machine installing the required components is not easy and documented somewhat cryptically. As a consequence, I decided to write the necessary steps down so that you can step through the easily.
- Download and install Python 3.5.3 from the official website. Tensorflow requires us to use version 3.5.x on windows so make sure that you don’t use 2.x or 3.6.x.
- Install scikit-learn, tensorflow and pydotplus from the command line: pip install scikit-learn pydotplus tensorflow If you are using a proxy call pip with the proxy parameter (e.g. pip –proxy http://user:email@example.com:8080 install scikit-learn pydotplus tensorflow)
- Install GraphViz from the official website and add its binary folder to your PATH variable (e.g. C:\Program Files (x86)\Graphviz2.38\bin).
- Download and install the compiled binaries for numpy 1.13 and scipy 0.19.0 from Christoph Gohlke‘s website. Higher versions might work as well. By downloading the pre-compiled binaries we avoid to install multiple compilers on our system. When downloading make sure to grab the right packages for Python 3.5 (…cp35…) and win64.
Install both packages using pip:
- pip install C:\Users\admin\Downloads\numpy-1.13.0rc2+mkl-cp35-cp35m-win_amd64.whl
- pip install C:\Users\admin\Downloads\scipy-0.19.0-cp35-cp35m-win_amd64.whl
Thats it, not you can use Scikit and Tensorflow on windows!