In an orbit near you
At the last PYPTUG meeting, I demoed Google's Tensorflow deep learning toolkit. I did that using the Jupyter notebook. If you are not familiar with this, check out try.jupyter.org and you'll be able to play with Python, R, Ruby, Scala, Bash etc.
To install jupyter on your computer, pip3 is your friend (more detail at http://jupyter.readthedocs.org/en/latest/install.html):
pip3 install jupyterBy installing jupyter, you'll also get the ipython kernel, so you'll be able to create new jupyter notebooks for python. There are over 50 programming languages supported by jupyter. But that is not all. You can also create specific environments and associate notebooks with them. It works great on pretty much any platform, including the Raspberry Pi, Windows, the Mac, Linux etc. Each kernel has a varying degree of availability, and the same can be said of python modules. Tensorflow will not run on the Pi at this time...
|New notebook dropdown in Jupyter 4|
If you've tried to install Tensorflow, particularly on a Mac, you have probably found it challenging, as Tensorflow requires Python 2.7.
brew install python
virtualenv -p /usr/local/bin/python2.7 tensor source tensor/bin/activate pip install numpy scipy sklearn pandas matplotlib pip install https://storage.googleapis.com/tensorflow/mac/tensorflow-0.5.0-py2-none-any.whl
(tensor)LTOXFDION:~ francois$ pip install ipython ipykernel LTOXFDION:kernels francois$ pwd /Users/francois/Library/Jupyter/kernels LTOXFDION:kernels francois$ ls ir python2 LTOXFDION:kernels francois$ cp -r python2/ tensor LTOXFDION:kernels francois$ cd tensor/ LTOXFDION:tensor francois$ vi kernel.json
In the editor you'll have to modify the path to python to point to your directory. If you dont have a python2 directory to copy, just create a tensor directory and create the kernel.json file. In the end, your kernel.json file should look something like:
You should be good to go now. Start jupyter:
You'll be able to create a new notebook for Tensorflow. From there, all you have to do is import it:
import tensorflow as tf
We'll continue on this next time.