I'm in the same situation than you (used to ruby, never used python). Using tensorflow through its high level API, tf.contrib.learn [1] has been easy enough. M

I'm in the same situation than you (used to ruby, never used python). Using tensorflow through its high level API, tf.contrib.learn [1] has been easy enough. Most of the actual work is about shaping data and tweaking hyper parameters (how many layers, how many neurons per layer, how many iterations, etc) which is just changing the value of variables, really. In order to build my dataset, I use ruby or golang and dump csv files. Tutorial code already shows how to load them in python. The most python I wrote was to figure out how to take a json string from command line argument and decode it, in order to make prediction after the training. This took me like fifteen minutes googling and trying, python is really accessible, especially if you're already used to ruby. Clearly, I do not recommend to do that for production code, but if you want to play with tensorflow and try to get skilled at vectorizing data and curating dataset (the most important tasks in all of this), you don't need to learn much about python. I do recommend though to take time and read lessons about neural networks, because you'll need proper knowledge about it to use tensorflow. [1] https://www.tensorflow.org/versions/r0.9/tutorials/tflearn/index.html https://www.tensorflow.org/versions/r0.9/tutorials/tflearn/i...