Posts

Showing posts from October, 2017

tensorflow-crash-course

Image
http://nicklocascio.com/tensorflow-crash-course I was recently tasked with teaching a  lecture  on TensorFlow to ~200 MIT students in 6.864 (Deep Learning for NLP). This post contains everything I taught them – and more. “Literally the best presentation, ever.” - random student during my presentation to 6.864 (before they fainted) TensorFlow Fundamentals Computation Graphs Everything in TensorFlow comes down to building a computation graph. What is a computation graph? Its just a series of math operations that occur in some order. Here is an example of a simple computation graph: A SIMPLE COMPUTATION GRAPH This graph takes 2 inputs, (a, b) and computes an output (e). Each node in the graph is an operation that takes some input, does some computation, and passes its output to another node. We could make this computation graph in TensorFlow in the following way: a = tf . placeholder ( tf . float32 ) b = tf . placeholder ( tf . float32 ) c = tf . add ( a ,