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BigML - Machine Learning Made Easy

BigML - Machine Learning Made Easy

Apache Mahout: Scalable machine learning and data mining Home | Skytree – Machine Learning on Big Data for Predictive Analytics OSCAR Project OSCAR allows users, regardless of their experience level with a *nix environment, to install a Beowulf type high performance computing cluster. It also contains everything needed to administer and program this type of HPC cluster. OSCAR's flexible package management system has a rich set of pre-packaged applications and utilities which means you can get up and running without laboriously installing and configuring complex cluster administration and communication packages. It also lets administrators create customized packages for any kind of distributed application or utility, and to distribute those packages from an online package repository, either on or off site. OSCAR installs on top of a standard installation of a supported Linux distribution. The default OSCAR setup is generally used for scientific computing using a message passing interface (MPI) implementation, several of which are included in the default OSCAR package set. OSCAR on! OSCAR 6.1.1 has been released! (Read more)

Mendel HMM Toolbox for Matlab Written by Steinar Thorvaldsen, 2004. Last updated: Jan. 2006. Dept. of Mathematics and Statistics University of Tromsø - Norway. steinart@math.uit.no MendelHMM is a Hidden Markov Model (HMM) tutorial toolbox for Matlab. To run the program you should make the following steps: 1. When you type "mendelHMM" in Matlab command window the main window of GUI will appear. Main window of the program. In his historic experiment, Gregor Mendel (1822-1884) examined 7 simple traits in the common garden pea (Pisum). Today we know that the recessive expressions most often are mutations in the DNA molecule of the gene, as it is well known for Mendel’s growth gene (trait 7) where a single nucleotide G is substituted with an A. In his experiment Mendel also studied in more detail the plant seeds with two and three heredity factors simultaneously. The estimate of a statistical model according to a training set There are two main types of learning. The sampling of new training data y = (A, A, a, a, a) 1. 2. 3.

Octave GNU Octave is a high-level interpreted language, primarily intended for numerical computations. It provides capabilities for the numerical solution of linear and nonlinear problems, and for performing other numerical experiments. It also provides extensive graphics capabilities for data visualization and manipulation. Octave is normally used through its interactive command line interface, but it can also be used to write non-interactive programs. The Octave language is quite similar to Matlab so that most programs are easily portable. Octave is distributed under the terms of the GNU General Public License. Version 4.0.0 has been released and is now available for download. An official Windows binary installer is also available from Thanks to the many people who contributed to this release!

Weka---Machine Learning Software in Java | Free software downloads DataGravity | Changing the game in data storage PVM: Parallel Virtual Machine PVM (Parallel Virtual Machine) is a software package that permits a heterogeneous collection of Unix and/or Windows computers hooked together by a network to be used as a single large parallel computer. Thus large computational problems can be solved more cost effectively by using the aggregate power and memory of many computers. The software is very portable. PVM enables users to exploit their existing computer hardware to solve much larger problems at minimal additional cost. Current PVM News: A new Russian translation of the site by Andrew Kovalev is available at New German translation of the site is available at The PVM website is now available in Belorussian provided by Fatcow. Current articles from PVM news group comp.parallel.pvm PVM Supported Architectures PVM Documentation: Project Overview A short overview of PVM and its features. HTML Man pages for PVM 3.3.

General Hidden Markov Model Library | Free Science & Engineering software downloads Weka 3 - Data Mining with Open Source Machine Learning Software in Java Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature. Weka is open source software issued under the GNU General Public License. Yes, it is possible to apply Weka to big data! Data Mining with Weka is a 5 week MOOC, which was held first in late 2013.

COC131 Data Mining, Tuotorials Weka "The overall goal of our project is to build a state-of-the-art facility for developing machine learning (ML) techniques and to apply them to real-world data mining problems. Our team has incorporated several standard ML techniques into a software "workbench" called WEKA, for Waikato Environment for Knowledge Analysis. With it, a specialist in a particular field is able to use ML to derive useful knowledge from databases that are far too large to be analysed by hand. WEKA's users are ML researchers and industrial scientists, but it is also widely used for teaching." Tutorial 01 (13/02/09) Get the old faithful data-set (.csv) here Get the tutorial 01 exercises here Get the tutorial 01 solutions here Statistics revision for Tutorial 01 here Tutorial 02 (20/02/09) Get the iris data-set (.arff) here Get the tutorial 02 exercises here Tutorial 03 (27/02/09) Get the tutorial 03 exercises here Tutorial 04 (06/03/09) Tutorial 03 exercises and clarification of any issues from earlier tutorials

GoodData | Experience SaaS Business Intelligence The Julia Language Online Code Repository The goal is to have working code for all the algorithms in the book in a variety of languages. So far, we have Java, Lisp and Python versions of most of the algorithms. There is also some old code in C++, C# and Prolog, but these are not being maintained. Supported Implementations We offer the following three language choices, plus a selection of data that works with all the implementations: Java: aima-java project, by Ravi Mohan. Unsupported Implementations Implementation Choices What languages are instructors recommending? Of course, neither recall nor precision is perfect for these queries, nor is the estimated number of results guaranteed to be accurate, but they offer a rough estimate of popularity.

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