Free data analysis software
data analysis software
Weka is a collection of machine learning algorithms for data mining tasks; with its own GUI.
(The application is named after a flightless bird of New Zealand that is very inquisitive.)
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. It is also well-suited for developing new machine learning schemes.
Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. With Vega, you can describe the visual appearance and interactive behavior of a visualization in a JSON format, and generate web-based views using Canvas or SVG.
Vega provides basic building blocks for a wide variety of visualization designs: data loading and transformation, scales, map projections, axes, legends, and graphical marks such as rectangles, lines, plotting symbols, etc. Interaction techniques can be specified using reactive signals that dynamically modify a visualization in response to input event streams.
Vega-Lite provides a higher-level grammar for visual analysis, comparable to ggplot or Tableau, that generates complete Vega specifications. Vega-Lite specifications consist of simple mappings of variables in a data set to visual encoding channels such as x, y, color, and size. These mappings are then translated into detailed visualization specifications in the form of Vega specification language. Vega-Lite produces default values for visualization components (e.g., scales, axes, and legends) in the output Vega Visualization Grammar specification using a rule-based approach, but users can explicit specify these properties to override default values.
D3 allows you to bind arbitrary data to a Document Object Model (DOM), and then apply data-driven transformations to the document. For example, you can use D3 to generate an HTML table from an array of numbers. Or, use the same data to create an interactive SVG bar chart with smooth transitions and interaction.
D3 is not a monolithic framework that seeks to provide every conceivable feature. Instead, D3 solves the crux of the problem: efficient manipulation of documents based on data. This avoids proprietary representation and affords extraordinary flexibility, exposing the full capabilities of web standards such as HTML, SVG, and CSS. With minimal overhead, D3 is extremely fast, supporting large datasets and dynamic behaviors for interaction and animation. D3’s functional style allows code reuse through a diverse collection of components and plugins.
RGraph is a HTML5 canvas graph library. It uses features that became available in HTML5 (specifically, the CANVAS tag) to produce a wide variety of graph types: bar chart, bi-polar chart (also known as an age frequency chart), donut chart, funnel chart, gantt chart, horizontal bar chart, LED display, line graph, meter, odometer, pie chart, progress bar, rose chart, scatter graph and traditional radar chart.
Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library. The library, largely written in Julia itself, also integrates mature, best-of-breed C and Fortran libraries for linear algebra, random number generation, signal processing, and string processing.
In addition, the Julia developer community is contributing a number of external packages through Julia’s built-in package manager at a rapid pace. IJulia, a collaboration between the IPython and Julia communities, provides a powerful browser-based graphical notebook interface to Julia.
It is based on libuv
Fluentd is a fully free and open-source log management tool that simplifies your data collection and storage pipeline. It eliminates the need to maintain a set of ad-hoc scripts.
ELKI: "Environment for Developing KDD-Applications Supported by Index-Structures" is a development framework for data mining algorithms written in Java. It includes a large variety of popular data mining algorithms, distance functions and index structures.
Its focus is particularly on clustering and outlier detection methods, in contrast to many other data mining toolkits that focus on classification. Additionally, it includes support for index structures to improve algorithm performance such as R*-Tree and M-Tree.
The modular architecture is meant to allow adding custom components such as distance functions or algorithms, while being able to reuse the other parts for evaluation.
Eclipse Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Apache Spark, DL4J brings AI to business environments for use on distributed GPUs and CPUs.
Easy, object oriented client side graphs for designers and developers. Open source HTML5 charts using the canvas tag. Chart.js is an easy way to include animated graphs on your website.
CatBoost is an open-source gradient boosting library with categorical features support
