Data Mining and Machine Learning: Concepts, Process, and Software Catalog

Data mining refers to the process of extracting hidden, previously unknown, and potentially valuable information from large volumes of data using algorithms.

It is closely related to computer science and employs methods such as statistics, online analytical processing, information retrieval, machine learning, expert systems, and pattern recognition.

Data mining is a hot research topic in artificial intelligence and databases, representing a non‑trivial decision‑support process that leverages AI, machine learning, pattern recognition, statistics, databases, and visualization to automatically analyze enterprise data, discover patterns, and aid decision‑making.

The knowledge discovery process consists of three stages: data preparation, data mining, and result expression and interpretation; it can interact with users or knowledge bases.

Typical data mining tasks include association analysis, clustering, classification, anomaly detection, subgroup discovery, and evolutionary analysis.

Machine learning is a multidisciplinary field that studies how computers can simulate or implement human learning behavior, drawing on probability theory, statistics, approximation theory, convex analysis, and algorithmic complexity.

It is the core of artificial intelligence, providing the fundamental means for computers to achieve intelligence.

Machine learning definitions vary, but commonly describe it as the scientific study of algorithms that improve automatically through experience, or as the use of data and past experience to optimize program performance.

Selected Data Mining and Machine Learning Software List

The following is an alphabetically organized catalog of software tools commonly used for data mining and machine learning.

Amazon Rekognition

Angoss

Anne O'Tate

Apache Flume

Apache MXNet

Aphelion (software)

BigDL

Caffe (software)

CellCognition

Chainer

Comparison of deep‑learning software

DADiSP

Data Mining Extensions

Deep Web Technologies

Deeplearning4j

Distributed R

Dlib

Encog

ELKI

Feature Selection Toolbox

FICO

Fluentd

Folding@home

General Architecture for Text Engineering

Apache Giraph

GNU Octave

GraphLab

Gremlin (programming language)

Ilastik

Information Harvesting

Jubatus

Julia (programming language)

Keras

KNIME

KXEN Inc.

L-1 Identity Solutions

LanguageWare

Lattice Miner

LIBSVM

Linguamatics

Apache Mahout

Mallet (software project)

Maple (software)

Massive Online Analysis

MATLAB

MeeMix

Megvii

Microsoft Cognitive Toolkit

ML.NET

Mlpack

Mlpy

ND4J (software)

ND4S

NetOwl

Neural Designer

Never‑Ending Language Learning

OpenNN

Oracle Data Mining

Orange (software)

Programming with Big Data in R

Picollator

Pipeline Pilot

Piranha (software)

Probabilistic Action Cores

PyTorch

R (programming language)

RapidMiner

Rattle GUI

Renjin

Rnn (software)

SAS (software)

Scikit-learn

Self‑Service Semantic Suite

SenseTime

Shogun (toolbox)

Sketch Engine

SolveIT Software

Apache Spark

SPSS Modeler

Apache SystemML

Tanagra (machine learning)

TensorFlow

List of text mining software

Torch (machine learning)

UIMA

VIGRA

Vowpal Wabbit

Waffles (machine learning)

Weka (machine learning)

Wolfram Language

Wolfram Mathematica

XGBoost

Yooreeka

Zeroth (software)