Topics /
The most popular blog posts about ai & machine learning on Hacker News. 97 posts.
A few weeks ago, I attended the Seven Pines Symposium on Fundamental Problems in Physics outside Minneapolis, where I had the honor of participating in a panel discussion with Sir Roger Penrose. T…
Learn how to access *multiple cameras* (including USB webcams and the Raspberry Pi camera module) using your Raspberry Pi, Python, and OpenCV.
Let's pretend we need to build a recommendation engine for an eCommerce web site. There are basically two approaches you can take: content-based and collaborative-filtering. We'll look at some...
In a previous post I wrote about how to build a ‘People Who Like This Also Like …’ feature for displaying lists of similar musicians. My goal was to show how simple Information Retrieval techniques can do a good job calculating lists of related artists. For instance, using BM25 distance on The Beatles shows the most…
Update 17/01: reddit discussion thread. Update 19/01: hacker news thread. The codex The Voynich Manuscript is a hand-written codex written in an unknown system and carbon-dated to the early 15th century (1404–1438). Although the manuscript has been studied by some famous cryptographers of the World War I and II…
An animated look at local maxima, novelty effects, differentiation, emergent maxima.
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.
プログラミングでは開発言語を用いて、アプリやWebサービス、業務システムなどを動かす仕組みを作ります。 将来プログラマーとして働きたいなら、まずは開発言語の基本から理解し、手を動かしながら学ぶことが近道です。 本サイトでは、初心者がつまずきやすい点を先回りして解消しつつ、焦らず段階的にスキルを積み上げる学習手順、職業訓練校の活用方法、復習や制作のコツまで具体的に整理して紹介します。
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...
📍 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
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
A Go implementation of a perceptron as the building block of neural networks and as the most basic form of pattern recognition and machine learning.
Imagine a contest in which we are going to pit man against machine. But instead of measuring who is best in playing the game of ‘Go’ we are going to measure who is fastest. In the one corner: Human, all of 175 pounds of extremely well trained runner. And in the other corner, a Formula 1 racecar with a remote control…
Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation. You can find the source on GitHub or you can read more about what Darknet can do right here:
Data files are derived from the Google Web Trillion Word Corpus , as described by Thorsten Brants and Alex Franz, and distributed by the Linguistic Data Consortium.
A step-by-step guide to make your computer a music expert.
