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Name: Ilya Dyachenko
Type: User
Twitter: flash_us
Ilya Dyachenko's Projects
fm-belief-network
Belief Networks for Fathom
functional-programming-in-scala
https://class.coursera.org/progfun-003/class/index
game-prototypes
JavaScript & CSS3 game prototypes
gitx
GitX (L) - A gitk clone for OS X
goose
Html Content / Article Extractor in Java open sourced from Gravity Labs - http://gravity.com
hackernews
There are way too many stories on Hacker News, and there's no option for "show me only the stories that Joel would like". So I built one. (Maybe "cobbled together" is more appropriate.)
hadoop-r
Example code for running R on Hadoop
haskellthehardway
hdevtools
Persistent GHC-powered background server for FAST haskell development tools
homebrew
The missing package manager for OS X.
humane-js
A simple, modern, browser notification system
instacss
speedy docs
interviewpuzzle
Cracking the coding interview puzzles...
investments
Helps you with managing your investments
iphonetracker
ipsur
IPSUR, Introduction to Probability and Statistics Using R, is a textbook written for an undergraduate course in probability and statistics. IPSUR is FREE, in the GNU sense of the word.
javascript-algorithms
📝 Algorithms and data structures implemented in JavaScript with explanations and links to further readings
js_jobs_bot
JS Jobs search telegram channel
julia
The Julia Language: a fresh approach to technical computing.
junk
Some set of random projects
kaggle-dsb2-keras
Keras tutorial for Kaggle 2nd Annual Data Science Bowl
kif
Keep It Functional - iOS Test Framework
klib
A standalone and lightweight C library
kod
Programmers' editor for OS X
learnhaskell
Learn Haskell
learning-react
The code samples for Learning React by Alex Banks and Eve Porcello, published by O'Reilly Media
light-haskell
Haskell plugin for LightTable
limit-order-book
Various implementations of limit order books (matching engines)
machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
machinelearninglectures
Code to demonstrate basic machine learning algorithms following on Stanford CS229.
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