A new word embedding paper came out of Google that promises to look at things missed by Word2Vec and Glove, provide a better understanding, and a better embedding. All word embedding schemes try to map a discrete word to a real vector. So if is your vocabulary, a word embedding is a function : Of course, the […]
Author Archive | Delip
On Reading Papers
One of the most important skill I learnt in grad school was to break down any complex paper into bite sized parts, digest them, and ask critical questions about them. On the face of it, it sounds like an obvious skill, right? Just like knowing how to talk doesn’t make you a good public speaker, […]
Universal Function Approximation using TensorFlow
A multilayered neural network with even a single hidden layer can learn any function. This universal function approximation property of multilayer perceptrons was first noted by Cybenko (1989) and Hornik (1991). In this post, I will use TensorFlow to implement a multilayer neural network (also known as a multilayer perceptron) to learn arbitrary Python lambda expressions. (more…)
Google TensorFlow: Updates & Lessons
TensorFlow came out today, and like the rest of the ML world, I buried myself with it. I have never been more excited about a new open source code. There are actionable tutorials etc. on the home page that’s worth checking out, but I wanted to know if this was yet another computational graph framework — […]