Oct/30/2018 Updated by


Python environment for Deep Learning

[Up] Japanese English

Make the python environment necessary to run the Deep Learning program.

  1. It is assumed that the environment of python 3.X has been installed on Anaconda. (X ≥ 7)
  2. Start "conda", and do the following steps in the "conda" window.
  3. Create a new python environment with conda. Here, the environment name is deep. At this moment, tensorflow runs only on python 3.6 or 3.5, so using 3.6.
  4.     (base) C:\Users\nitta>  conda create -n deep python=3.6 jupyter 
  5. Switch the new python environment.
  6.     (deep) C:\Users\nitta>  conda activate deep  
  7. Install tensorflow
  8.     (deep) C:\Users\nitta>  pip install --ignore-installed --upgrade tensorflow  
  9. There may be a message saying to update the pip during installation of tensorflow. In that case, update pip according to the instructions.
  10. Install keras
  11.     (deep) C:\Users\nitta>  pip install keras  
  12. Install convenient modules
  13.     (deep) C:\Users\nitta>   pip install scipy scikit-learn pillow h5py matplotlib pandas  
  14. Install OpenCV
  15.     (deep) C:\Users\nitta>  conda install opencv  
  16. Install Natural Language ToolKit
  17.     (deep) C:\Users\nitta>  pip install nltk  
  18. Install gensim for word2vec
  19.     (deep) C:\Users\nitta>  pip install gensim