Chapter 8. Dive into TensorFlow with Linux
For the last eight months, I have spent a lot of time trying to absorb as much as I can about machine learning. I am constantly amazed at the variety of people I meet on online MOOCs in this small but quickly growing community, from quantum researchers at Fermilab to Tesla-driving Silicon Valley CEOs. Lately, I have been putting a lot of my focus into the open source software TensorFlow, and this tutorial is the result of that.
I feel like a lot of machine learning tutorials are geared toward Mac. One major advantage of using Linux is it’s free and it supports using TensorFlow with your GPU. The accelerated parallel computing power of GPUs is one of the reasons for such major advancements in machine learning. You don’t need cutting-edge technology to build a fast image classifier; my computer and graphic card cost me less than $400 USD.
In this tutorial, I am going to walk you through how I learned to train my own image classifier on Ubuntu with a GPU. This tutorial is very similar to Pete Warden’s “TensorFlow for Poets”, but I did things a little differently. I am going to assume that you have TensorFlow and Bazel installed and have cloned the latest TensorFlow release in your home directory. If you have not yet done that, you can follow a tutorial on my blog. If you don’t have a compatible GPU, you can still follow this tutorial; it will just take longer.
The overall process is extremely simple and can be broken into ...