Below are the steps to setup your development environment for Deep learning :
1.) Download and Install Anaconda from here :https://www.continuum.io/downloads
2.) Create a conda environment for data science development so that it doesn't affect the other install components .
conda create -n tensor_keras_py3.5 python=3.5 pandas scikit-learn jupyter matplotlib
3.) Activate the created environment
source activate tensor_keras_py3.5
4.) Install tensorflow inside activated env.
pip install tensorflow
5.) Install keras inside activated env.
pip install keras
6.) Install opencv inside activated env.
pip install opencv-python
7.) Install IMUTILS
pip install imutils
Test your environment
1.) Type ipython in the shell , which should open ipython console .
2.) Type import tensorflow,keras , it should reply using tensorflow backend
Switching keras backend from Tensorflow to theano
keras backend is set in a hidden file stored in your home path . You can find it at $/.keras/keras.json . You can open it with a text editor and you should see something like this :
{ "image_dim_ordering": "tf", "epsilon": 1e-07, "floatx": "float32", "backend": "tensorflow" }
You can change backend to theano . save it and close it . Now if you open ipython and do import keras then it will return using theano backend .
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