Conda environments

Using pip may be the quickest to get started, but I see that the most convenient method involves using conda environments.

Conda environments allow you to create isolated Python environments, which are completely separate from your system Python or any other Python programs. This way, there is no chance of your TensorFlow installation messing with anything already installed, and vice versa.

To use conda, you must download Anaconda from here: https://www.anaconda.com/download/. This will include conda with it. Once you've installed Anaconda, installing TensorFlow can be done by entering the certain commands in your Command Prompt.
First, enter the following:

    $ conda create -n tf_env pip python=3.5

This will create your conda environment with the name tf_env, the environment will use Python 3.5, and pip will also be installed for us to use.

Once this environment is created, you can start using it by entering the following on Windows:

    $ activate tf_env

If you are using Ubuntu, enter the following command:

    $ source activate tf_env

It should now display (tf_env) next to your Command Prompt. To install TensorFlow, we simply do a pip install as previously, depending on if you want CPU only or you want GPU support:

    (tf_env)$ pip install --upgrade tensorflow
    (tf_env)$ pip install --upgrade tensorflow-gpu