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The central principle of D3.js design is to enable the programmer to first use a CSS-style selector to select a given set of Document Object Model (DOM) nodes, then use operators to manipulate them in a similar manner to jQuery. [8]
Vega acts as a low-level language suited to explanatory figures (the same use case as D3.js), while Vega-Lite is a higher-level language suited to rapidly exploring data. [3] Vega is used in the back end of several data visualization systems, for example Voyager.
MALLET is an integrated collection of Java code useful for statistical natural language processing, document classification, cluster analysis, information extraction, topic modeling and other machine learning applications to text.
Weka – machine-learning algorithms that can be integrated in KNIME; ELKI – data mining framework with many clustering algorithms; Keras - neural network library; Orange - an open-source data visualization, machine learning and data mining toolkit with a similar visual programming front-end; List of free and open-source software packages
interactive phylogenetic tree visualization with numerical annotation graphs, with SVG or PNG output, implemented in D3.js [44] phylotree.js Javascript phylotree.js is a library that extends the popular data visualization framework D3.js, and is suitable for building JavaScript applications where users can view and interact with phylogenetic trees
Multidimensional scaling (MDS) is a means of visualizing the level of similarity of individual cases of a data set. MDS is used to translate distances between each pair of objects in a set into a configuration of points mapped into an abstract Cartesian space.
DVC is a free and open-source, platform-agnostic version system for data, machine learning models, and experiments. [1] It is designed to make ML models shareable, experiments reproducible, [2] and to track versions of models, data, and pipelines. [3] [4] [5] DVC works on top of Git repositories [6] and cloud storage. [7]
JAX is a machine learning framework for transforming numerical functions developed by Google with some contributions from Nvidia. [2] [3] [4] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and OpenXLA's XLA (Accelerated Linear Algebra).