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Taming Recurrent Neural Networks for Better Summarization
This blog post is about the ACL 2017 paper Get To The Point: Summarization with Pointer-Generator Networks by Abigail See, Peter J Liu, and Christopher Manni...
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Neuralink and the Brain's Magical Future
I knew the future would be shocking but this is a whole other level.
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Deep Learning without Backpropagation
A machine learning craftsmanship blog.
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The Amazing Power of Word Vectors (2016)
For today’s post, I’ve drawn material not just from one paper, but from five! The subject matter is ‘word2vec’ – the work of Mikolov et al. at Google on efficient vect…
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Generating faces of cats using Generative Adversarial Networks
I experimented with generating faces of cats using Generative adversarial networks (GAN). I wanted to try DCGAN, WGAN and WGAN-GP in low and higher resolutions. I used the CAT dataset (yes this is …
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A Guide to Synthesizing Adversarial Examples
Synthesizing adversarial examples for neural networks is surprisingly easy.
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Capsule Networks Explained
Assumed Knowledge: Convolutional Neural Networks, Variational Autoencoders Disclaimer: This article does not cover the mathematics behind Capsule Networks, but rather the intuition and motivation behind them. What are Capsule Networks and why do they exist? The Capsule Network is a new type of neural network…
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An Adversarial Review of “Adversarial Generation of Natural Language”
Or, for fucks sake, DL people, leave language alone and stop saying you solve it.
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Teaching an AI to play a simple game using Q-learning
In this post I will walk you through how to teach a computer to master a simple video game using the q-learning reinforcement learning algorithm. We will implement the algorithm from scratch in Ruby without the use of external gems. To enable us to illustrate the inner workings of the algorithm we will be teaching […]
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How people talk about marijuana on Reddit: a natural language analysis
In honor of today being April 20th, I thought it would be interesting to do some NLP on Reddit comments about marijuana (shout out to…
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Language Models, Word2Vec, and Efficient Softmax Approximations
The Word2Vec model has become a standard method for representing words as dense vectors. This is typically done as a preprocessing step, after which the learned vectors are fed into a discriminative model (typically an RNN) to generate predictions such as movie review sentiment, do machine translation, or even…
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A Comparison of Distributed Machine Learning Platforms
This paper surveys the design approaches used in distributed machine learning (ML) platforms and proposes future research directions. This ...
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The impossibility of intelligence explosion
In 1965, I. J. Good described for the first time the notion of “intelligence explosion”, as it relates to artificial intelligence (AI):
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Neural Network on a Commodore 64 (1987)
Neural Network on a Commodore 64
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A Theory of Sequence Memory in Neocortex
Why neurons have thousands of synapses, a theory of sequence memory in neocortex Hawkins & Ahmad, Front. Neural Circuits 2016 It all began with a fascinating lunchtime conversation with Martin …
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Understanding LSTM Networks (2015)
Humans don’t start their thinking from scratch every second. As you read this essay, you understand each word based on your understanding of previous words. You don’t throw everything away and start thinking from scratch again. Your thoughts have persistence.
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Keras and deep learning on the Raspberry Pi
In this guide you'll learn how to perform real-time deep learning on the Raspberry Pi using Keras, Python, and TensorFlow.
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Empirical Bayes for multiple sample sizes
The James-Stein Estimator with unequal variances
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