Generating Recommendations at Amazon Scale with Apache Spark and Amazon DSSTNE
In this post, I discuss an alternate solution; namely, running separate CPU and GPU clusters, and driving the end-to-end modeling process from Apache Spark.
Every blog post that took off on Hacker News, ranked by the votes of its best submission. 250 posts.
In this post, I discuss an alternate solution; namely, running separate CPU and GPU clusters, and driving the end-to-end modeling process from Apache Spark.
I’m just going to jump right into the definitions and rigor, so if you haven’t read the previous post motivating the singular value decomposition, go back and do that first. This post will be theorem, proof, algorithm, data. The data set we test on is a thousand-story CNN news data set. All of the data, code, and…
About two weeks ago we released ColorizeBot to wander around Reddit. This Reddit bot has started by coloring images on r/OldSchoolCool and a day after, spread all over Reddit. The bot was based on a pre-trained neural network - More information on the netwrok can be found here. After
Towards deep symbolic reinforcement learning Garnelo et al, 2016 Every now and then I read a paper that makes a really strong connection with me, one where I can’t stop thinking about the imp…
Ever since I learned about neural networks playing Atari games I wanted to reimplemnted it and learn how it works. Below you can see an AI playing Space Invaders. I trained it during my batch at Recurse Center on little over 50M frames.
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Gradient descent is a standard tool for optimizing complex functions iteratively within a computer program. Its goal is: given some arbitrary function, find a minumum. For some small subset of functions - those that are convex - there's just a single minumum which also happens to be global. For most realistic…
In my previous post , I described some experiments I was doing to reduce images to a Bag of Visual Words (BOVW) . My goal is to build a Con...
The latest information about the Unconference is now available at the Unconference wiki, which will be periodically updated with more information for attendees.
📍 This article has moved. Read the current version at This is the third part in a short series of blog posts about quantum Monte Carlo (QMC). The series is derived from an introductory lecture I ga…
A PROPOSAL FOR THE DARTMOUTH SUMMER RESEARCH PROJECT ON ARTIFICIAL INTELLIGENCE
I have a new draft paper with Aylin Caliskan-Islam and Joanna Bryson titled Semantics derived automatically from language corpora necessarily contain human biases. We show empirically that natural language necessarily contains human biases, and the paradigm of training machine learning on language corpora means that…
MusicNet is the first publicly available large-scale classical music dataset designed to allow machine learning algorithms to tackle everything from automated m
Posted by Jon Shlens, Senior Research ScientistAt the end of last year we released code that allows a user to classify images with TensorFlow model...
At Meta, research permeates everything we do. We believe the most interesting research questions are derived from real world problems.
Its been quite some time since I wrote a Data Mining post . Today, I intend to post on Mean Shift – a really cool but not very well known algorithm. The basic idea is quite simple but the results a…
When you play Chess, there are on average something like 30 different moves you can make each turn. In other words, the branching factor is ...
Reconstructing films with artificial neural networks