Gourt > Computers > Artificial Intelligence > Machine Learning > Software
Computer software (or simply software) is the programs and procedures that enable a computer to perform a specific task, as opposed to the physical components of the system (hardware). This includes application software such as a word processor, which enables a user to perform a task, and system software such as an operating system, which enables other software to run properly, by interfacing with hardware and with other software.
The term "software" was first used in this sense by John W. Tukey in 1957. In computer science and software engineering, computer software is all information processed by computer systems, programs and data. The concept of reading different sequences of instructions into the memory of a device to control computations was invented by Charles Babbage as part of his difference engine. The theory that is the basis for most modern software was first proposed by Alan Turing in his 1935 essay Computable numbers with an application to the Entscheidungsproblem. Hally, Mike (2005:79). Electronic brains/Stories from the dawn of the computer age. British Broadcasting Corporation and Granta Books, London. ISBN 1-86-207663-4.
Relationship to hardware
Computer software is so called in contrast to computer hardware, which encompasses the physical interconnections and devices required to store and execute (or run) the software. In computers, software is loaded into RAM and executed in the central processing unit. At the lowest level, software consists of a machine language specific to an individual processor. A machine language consists of groups of binary values signifying processor instructions (object code), which change the state of the computer from its preceding state. Software is an ordered sequence of instructions for changing the state of the computer hardware in a particular sequence. It is generally written in high-level programming languages that are easier and more efficient for humans to use (closer to natural language) than machine language. High-level languages are compiled or interpreted into machine language object code. Software may also be written in an assembly language, essentially, a mnemonic representation of a machine language using a natural language alphabet. Assembly language must be assembled into object code via an assembler. More on [ Computer software ]
Would you pay $60 for 25,000 targeted followers? That is all I paid for my Twitter software. http://cli.gs/NV6Xgr
steveb2u (Steve B) Wed, 04 Nov 2009 13:16:59 -0000
Would you pay $60 for 25,000 targeted followers? That is all I paid for my Twitter software. http://cli.gs/NV6Xgr
@fruitdance Yup they did... Didn't set my alarm yet magically woke up at 4am to watch it, lol I need to find some recording software for it
purplechar (Charlotte Negus) Wed, 04 Nov 2009 13:16:58 -0000
@fruitdance Yup they did... Didn't set my alarm yet magically woke up at 4am to watch it, lol I need to find some recording software for it
Total 3D Home Design Deluxe 8.0 - ..:: Network Download ::..: Free software downloads and software reviews - Ne.. http://bit.ly/3WldWC
nevkarn (Nevada Karyan) Wed, 04 Nov 2009 13:16:50 -0000
Total 3D Home Design Deluxe 8.0 - ..:: Network Download ::..: Free software downloads and software reviews - Ne.. http://bit.ly/3WldWC
Total 3D Home Design Deluxe 8.0 - ..:: Network Download ::..: Free software downloads and software reviews - Ne.. http://bit.ly/18sgRO
nevkarn (Nevada Karyan) Wed, 04 Nov 2009 13:16:46 -0000
Total 3D Home Design Deluxe 8.0 - ..:: Network Download ::..: Free software downloads and software reviews - Ne.. http://bit.ly/18sgRO
Que sÃ, que software libre no tiene por qué ser gratuito, pero ¿cuántos del gran público tienen claro este matiz?
pentacour (pentacour) Wed, 04 Nov 2009 13:16:43 -0000
Que sí, que software libre no tiene por qué ser gratuito, pero ¿cuántos del gran público tienen claro este matiz?
RT: @henriquebastos: Ãltimas vagas para o tutorial Welcome to the Django na II Ultra Maratona de Software Livre http://bit.ly/2HBMoN #django
rafaelp (Rafael Lima) Wed, 04 Nov 2009 13:16:42 -0000
RT: @henriquebastos: Últimas vagas para o tutorial Welcome to the Django na II Ultra Maratona de Software Livre http://bit.ly/2HBMoN #django
ANNI - Artificial Neural Network Investing - Commercial Securities Modeler that uses artificial neural networks and genetic algorithms for customizable prediction
Meta Description: [ Advanced Neural Network Investing Program (Stock Trading Software) using Advanced Technologies for the ultimate in stock prediction and portfolio management. ]
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AutoClass - Takes a database of cases described by a combination of real and discrete valued attributes, and automatically finds the natural classes in that data. It can be seen as a Naive Bayes classifier where the class node is hidden. [Free]
Bayes Net Toolbox for Matlab - Supports several inference algorithms and learning algorithms. Allows simulation of static and dynamic networks, including HMMs, IOHMMs, and Kalman filters.
Bayes++ - A library of C++ classes for Bayesian filtering. From the Australian Centre for Field Robotics. [C++, MIT license]
Bayesian Essay Test Scoring System (BETSY) - A freeware windows-based program that classifies text based on trained material. Designed for automated essay scoring, BETSY can be applied to any text classification task.
Meta Description: [ BETSY is a windows-based program designed for automated essay scoring and can be applied to any text classification task. ]
C4.5 and FOIL - Home page of R. Quinlan. FTP links to FOIL (inductive logic programming) and C4.5 (learning decision trees).
Classification Toolbox for MATLAB - A site by Elad Yom-Tov, co-author of the toolbox, that contains additions and updates to the toolbox, as well as a discussion board
Meta Description: [ Elad Yom-Tov's homepage ]
EM algorithm for Mixture models - Shotaro Akaho's implementation of EM algorithm for modeling Mixtures of Gaussians (Java, free). An extended version is available from the author.
Experience-Based Language Acquisition - Computational model of human language acquisition written in Java; currently acquires a protolanguage of nouns and verbs language based on visual perception
Meta Description: [ The world's largest development and download repository of Open Source code and applications ]
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FastMix - Generates Gaussian mixture models for large datasets using efficient EM clustering algorithms. [Free]
GNU Hidden Markov Model Library - Hidden Markov Models software library from the Center of Applied Informatics, Cologne. Includes algorithms such as Viterbi, Baum-Welch, and Forward-Backward. [C, GPL license]
Meta Description: [ The world's largest development and download repository of Open Source code and applications ]
HMM and other statistical programs - On this page an imlementation of Hidden Markov Models and an application to part-of-speech tagging. Also available a multivariate hypothesis testing software for Gaussian Data and TRUEVIZ: A groundtruth/metadata Editing and Visualizing Toolkit for OCR.
HMMER - Sean Eddy's lab, present profile hidden Markov models for biological sequence analysis, a tool used to build HMMs from multiple alignments, and calculate e-scores.
Incremental Decision Tree Induction - An algorithm that incrementally constructs decision trees from labeled examples. [Free for individual research purposes]
libbpfl - Bayesian Probability Filtering Library - A general purpose library for Bayesian filtering. [C++, LGPL license]
LNKnet Pattern Classification Software - A software package developed at MIT Lincoln Laboratory which integrates more than 20 neural network, statistical, and machine learning classification, clustering, and feature selection algorithms into a modular software package. [Public domain license]
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Machine Learning Packages from the CMU Artificial Intelligence Repository - Links to FTP repositories including ACCEL, CLASSWEB, FOCL, FOIL, GOLEM, INDEX, MILES, MOBAL, OC1, Occamn, PEBLS, RWM.
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Machine Learning Programs by Peter Clark - QM: Guiding inductive learning with a Qualitative Model. LPE: Lazy Partial Evaluation. CN2: Rule induction from examples. [Free]
Meta-MEME v2.0.1 - Software toolkit for building and using motif-based hidden Markov models of DNA and proteins - from the Univ. of California-San Diego.
MIX - Software for learning Mixture Distributions. Commercial license.
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Multiple EM for Motif Elicitation and Motif Alignment and Search Tool (MEME/MAST) - MEME System is a program for discovering motifs in groups of related DNA or protein sequences. MAST is a tool for searching biological sequence databases for sequences that contain one or more of a group of known motifs.
N-gram Statistics Package (NSP) - Suite of Perl tools for counting and analyzing word n-grams in text; provides standard tests of association for identifying word n-grams in large corpora and allows users to implement other tests with minimal Perl knowledge.
Observable Operator Modeling Kit - Machine learning library for Observable Operator Models (OOMs) suitable for time-series and sequence data classification and prediction. OOMs are similar but more powerful than HMMs. [C++, BSD license]
Pattern Recognition Application Programmer's Interface (PRAPI) - A C++ library for many pattern recognition tasks; main focus is on image analysis, but a general architecture and XML-based data interchange format allows it to be used for many other tasks as well.
Pfam - A large collection of multiple sequence alignments and trained hidden Markov models covering many common protein domains.
500
PRODIGY System - An architecture for planning and learning. [Free]
Sequence Alignment and Modeling System (SAM) - A collection of tools for creating and using HMMs for biological sequences. Free license for academic and nonprofit usages.
SNoW - A learning architecture specifically taylored for learning in very high-dimensional feature spaces. The current release uses sparse variations of Winnow, Perceptron, and Naive Bayes. Free for personal academic and research purposes.
Software Packages for Graphical Models/Bayesian Networks - Directory of software tools for modeling graphs and Bayesian networks. Some have learning capabilities.
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Statistical Decision Trees - A program for inducing Bayesian decision trees. Applications to speech. [Free]
SUBDUE Knowledge Discovery in Structural Databases - The program discovers interesting and repetitive subgraphs in a labeled graph representation using the minimum description length principle. Applications to molecular biology. [Free]
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The Bow Toolkit - A library of C code useful for writing statistical text analysis, language modeling and information retrieval programs. The current distribution includes the library, as well as front-ends for document classification (rainbow), document retrieval (arrow) and document clustering (crossbow). [Free]
The CHILL Empirical Parser Acquisition System - A general approach to the problem of inducing natural language parsers. It uses an annotated corpus, and produces a parser by using ILP for inducing the rules that control the actions of a shift-reduce parser. [Free]
The NEITHER Theory Revision System - A propositional theory refinement system that will modify a incomplete or incorrect rule base so as to make it consistent with a set of input training examples. [Free]
Tilburg Memory Based Learner (TIMBL) - A program implementing several memory-based learning techniques. These learners store representation of the training set explicitly, and classifies new cases by extrapolation from the most similar stored cases. Free for educational or non-commercial research purposes.
TRON - A learning computer player for the light cycles game in Tron
Weka 3 - Open Source Machine Learning Software in Java - Suite that implements decision trees and tables, rule learners, Naive Bayes, support vector machines, voted perceptrons, multi-layer perceptron. Meta schemes include bagging, stacking, and boosting. [Free under GPL]
WinMine Toolkit - Tools for learning dependency networks or Bayesian networks from data. [Free]
XELOPES Data Mining Library - Platform- and data-source-independent library for embedded data mining based on the CWM/OMG and other data mining standards. XELOPES-Java algorithms: SVMs, market basket analysis, sequence analysis, decision trees, cluster analysis, multidimensional grouping. XELOPES-C++ algorithms: SVMs, decision trees. [GPL]
Meta Description: [ prudsys AG, Data Mining Software and -Consulting ]
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