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jquery-highcharttable-plugin

jQuery plugin to convert HTML tables to HighCharts graphs

kafka-web-console

A web console for Apache Kafka

kaggle-advertised-salaries

Predicting job salaries from ads - a Kaggle competition

kaggle-blackbox

Deep learning made easy

kaggle-criteo

Kaggle Criteo https://www.kaggle.com/c/criteo-display-ad-challenge

kaggle-event

Event Recommendation Engine Challenge

kaggle-event-recommendation

Model for the Event Recommendation Engine Challenge on Kaggle.com

kaggle-event-recommendation-1

kaggle-galaxies

Winning solution for the Galaxy Challenge on Kaggle (http://www.kaggle.com/c/galaxy-zoo-the-galaxy-challenge)

kaggle-job-salary

My submission to Kaggle job salary prediction

kaggle-ndsb-visualization

Scripts to visualize the Kaggle NDSB training images

kaggle-stumbleupon

bag of words + sparsenn

kaggle_loan_default_prediction

R code for Kaggle's Loan Default Prediction - Imperial College London challenge

kaggle_the_hunt_for_prohibited_content

Code for Kaggle's The Hunt for Prohibited Content Competition

kairos

Python module for time series data in Redis and Mongo

kdd-cup-2013-track1

KDD CUP 2013 - Track 1 - 2nd place model

kibana

Kibana 3

kindle-open-books

This project is created to convert open source materials to kindle supported format

landslide

Generate HTML5 slideshows from markdown, ReST, or textile

lggr

Python Logging for Humans

liblbfgs

libLBFGS: a library of Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS)

lijinhui.github.com

blog

log

log

machinelearninginaction

Source Code for the book: Machine Learning in Action published by Manning

madlib

Open-source library for scalable in-database analytics.

marisa-trie

Static memory-efficient Trie-like structures for Python (2.x and 3.x). Uses marisa-trie C++ library.

maximum-awesome

Config files for vim and tmux.

mdrill

for千亿数据即席分析

metrics

Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave

ml_for_hackers

Code accompanying the book "Machine Learning for Hackers"