jtth + algorithm   23

Summary of all the MIT Introduction to Algorithms lectures - good coders code, great reuse
As you all may know, I watched and posted my lecture notes of the whole MIT Introduction to Algorithms course. In this post I want to summarize all the topics that were covered in the lectures and point out some of the most interesting things in them.

Actually, before I wrote this article, I had started writing an article called “The coolest things that I learned from MIT’s Introduction to Algorithms” but quickly did I realize that what I was doing was listing the topics in each article and not really pointing out the coolest things. Therefore I decided to write a summary article first (I had promised to do so), and only then write an article on really the most exciting topics.

Talking about the summary, I watched a total of 23 lectures and it resulted in 14 blog posts. It took nearly a year to publish them here. The first blog post in this series was written in August 2008, and the last in July 2009.
cs  computersciene  mit  algorithm  algorithms 
november 2009 by jtth
Snowball
Snowball is a language in which stemming algorithms can be easily represented. The Snowball compiler translates a Snowball script (a .sbl file) into either a thread-safe ANSI C program or a Java program. For ANSI C, each Snowball script produces a program file and corresponding header file (with .c and .h extensions). The language has a full manual, and the various stemming scripts act as example programs.
software  development  free  library  research  tools  programming  python  ai  search  tool  language  java  algorithms  linguistics  text  algorithm  c  nlp  searchengine  classification  ir  stem  porter  stemmer  stemming  stopwords  lucene  textmining  snowball 
july 2009 by jtth
Introduction to Information Retrieval
The book aims to provide a modern approach to information retrieval from a computer science perspective. It is based on a course we have been teaching in various forms at Stanford University and at the University of Stuttgart.
reference  programming  web  research  free  search  algorithms  data  information  algorithm  ai  cs  books  book  ebooks  ebook  pdf  searchengine  nlp  clustering  datamining  ir  classification  machinelearning 
july 2009 by jtth
DM's Esoteric Programming Languages - Intelligent Design Sort
The probability of the original input list being in the exact order it's in is 1/(n!). There is such a small likelihood of this that it's clearly absurd to say that this happened by chance, so it must have been consciously put in that order by an intelligent Sorter. Therefore it's safe to assume that it's already optimally Sorted in some way that transcends our naïve mortal understanding of "ascending order". Any attempt to change that order to conform to our own preconceptions would actually make it less sorted.
funny  design  humor  programming  algorithms  geek  algorithm  religion  creationism 
april 2009 by jtth
Backpropagation
The project describes teaching process of multi-layer neural network employing backpropagation algorithm. To illustrate this process the three layer neural network with two inputs and one output,which is shown in the picture below, is used:
programming  computer  tutorial  math  network  ai  mathematics  computerscience  algorithm  algorithms  neural  networks  neuralnetworks  nn  ann  machinelearning  backpropagation 
december 2008 by jtth
Damn Interesting » On the Origin of Circuits
It seems that evolution had not merely selected the best code for the task, it had also advocated those programs which took advantage of the electromagnetic quirks of that specific microchip environment. The five separate logic cells were clearly crucial to the chip's operation, but they were interacting with the main circuitry through some unorthodox method– most likely via the subtle magnetic fields that are created when electrons flow through circuitry, an effect known as magnetic flux. There was also evidence that the circuit was not relying solely on the transistors' absolute ON and OFF positions like a typical chip; it was capitalizing upon analogue shades of gray along with the digital black and white.
science  article  design  programming  cool  interesting  computer  technology  research  algorithm  computing  antenna  genetic  biology  nasa  hardware  ai  electronics  history  evolution  circuitry 
december 2008 by jtth
SourceForge.net: ImproSculpt
Software for live sampling and audio processing. Algorithmic composition and improvised audio manipulation in real time. The audio engine uses Csound, and the composition logic is built with Python.
software  tools  audio  jazz  phd  dissertation  improvisation  algorithm  python  csound 
november 2008 by jtth
Notes on Introduction To Algorithms | Lambda the Ultimate
Peteris Krumins has been posting his notes on MIT’s Introduction to Algorithms. The notes are valuable for anyone interested in working their way through the CLRS text and MIT Open Courseware videos.
video  programming  opencourseware  notes  mit  learning  education  algorithms  algorithm  computerscience 
october 2008 by jtth
Open source Clustering software
Cluster 3.0 provides a Graphical User Interface to access to the clustering routines. It is available for Windows, Mac OS X, and Linux/Unix. Python users can access the clustering routines by using Pycluster, which is an extension module to Python.
algorithm  algorithms  analysis  cluster  code  comparison  complexity  clustering  software  opensource  statistics  python  datamining  programming  tools 
july 2008 by jtth
Rushkoff's algorithm - The Boston Globe
The 22-letter alphabet did not lead to a society of literate Israelite readers, but a society of hearers, who would gather to hear the Torah scroll read to them by a priest.
rushkoff  algorithm  media  control  web  blog  blogging  graphic  society  formula 
march 2008 by jtth
Yann LeCun's news
Convolutional Neural Networks are are a special kind of multi-layer neural networks. Like almost every other neural networks they are trained with a version of the back-propagation algorithm. Where they differ is in the architecture.
neuralnetwork  neural  network  ocr  algorithm  machine-learning  machine  learning  vision 
march 2008 by jtth

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