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— from the Kagglers' Favorite Tools blog post, where we do a survey of our competitors to find their favourite tools.
How I Did It Archive
The teams that win our competitions regularly post on our blog, giving an overview of how they won and the tools they used.
R is a popular language and environment for statistical computing and graphics.
Apeks.io is a machine learning tools for data classification and prediction. Apeks.io has a great collection of machine learning algorithms.
Weka is a collection of machine learning algorithms for data mining tasks, in Java.
Cascading is an Apache Licensed software abstraction layer for Apache Hadoop for creating complex workloads and queries.
Apache Licensed, Java- and Hadoop-based scalable machine learning library.
An open source scalable machine learning server for programmers and data engineers to build smart software. It is algorithm-agnostic and has built-in support to Apache Mahout.
GNU Octave is a high-level language, primarily intended for numerical computations — A.K.A. "Free MATLAB".
A Factorization Machine Library by Steffen Rendle, winner of the Grockit competition.
An optimized general purpose gradient boosting library. The library is parallelized using OpenMP. It implements machine learning algorithm under gradient boosting framework, including generalized linear model and gradient boosted regression tree. It supports various objective functions, including regression, classification and ranking. The package is also made to be extensible, so that users are also allowed to define their own objectives easily. Besides the standalone console version, you can use XGBoost in python, R and Julia
A parallel framework for machine learning, has many collaborative filtering algorithms.
MyMediaLite is a lightweight, multi-purpose library of recommender system algorithms.
A scalable real-time recommender engine platform, evolved from Apache Mahout. The single-machine Serving Layer is free and open source.
The pseudo-random generator with the coolest-sounding name, and that's why you should use it (in addition to its other redeeming qualities).
SciLua is a framework for general purpose scientific computing based on LuaJIT. It includes vector/matrix algebra, random number generators/distributions, root finding and optimisation algorithms, automatic differentiation, others ... Also included a module to interface with R.
Torch7 is a scientific computing framework with wide support for machine learning algorithms, similar to Matlab/Octave, but ANN focused.
A Pattern Recognizer In Lua with Artificial Neural Networks is recently and in development open source tool which allows to train ANNs among other machine learning models for a wide range of pattern recognition tasks.
A hyperparameter optimization framework implemented in Python. Useful to estimate hyperpara,eters like learning rate, momentum, hidden layer sizes, ...
Alpine is a visual and collaborative environment for building powerful end to end workflows (data mining, exploratory analysis, modeling, and scoring) with support for many databases and Hadoop.
MATLAB (matrix laboratory) is a numerical computing environment and programming language.
Neural Designer is a professional application for predictive analytics which transforms raw data in useful knowledge through trained neural networks.
Machine Learning and advanced analytics engine, designed to accurately process massive datasets at high speeds.
Last Updated: 2014-10-22 06:49 by sergiointelnics
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