Oct/30/2018 Updated by
Python environment for Deep Learning
Make the python environment necessary to run the Deep Learning program.
- It is assumed that the environment of python 3.X has been installed on Anaconda. (X ≥ 7)
- Start "conda", and do the following steps in the "conda" window.
- 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.
(base) C:\Users\nitta> conda create -n deep python=3.6 jupyter
- Switch the new python environment.
(deep) C:\Users\nitta> conda activate deep
- Install tensorflow
(deep) C:\Users\nitta> pip install --ignore-installed --upgrade tensorflow
- There may be a message saying to update the pip during installation of tensorflow.
In that case, update pip according to the instructions.
- Install keras
(deep) C:\Users\nitta> pip install keras
- Install convenient modules
(deep) C:\Users\nitta> pip install scipy scikit-learn pillow h5py matplotlib pandas
- Install OpenCV
(deep) C:\Users\nitta> conda install opencv
- Install Natural Language ToolKit
(deep) C:\Users\nitta> pip install nltk
- Install gensim for word2vec
(deep) C:\Users\nitta> pip install gensim