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The scikit-learn Python library has proven very popular with machine learning researchers and data scientists in the last five years. It provides a uniform interface for training and using models, as well as a set of tools for chaining (pipelines), evaluating, and tuning model hyperparameters. ScikitLearn.jl brings these capabilities to Julia. Its primary goal is to integrate both Julia- and Python-defined models together into the scikit-learn framework.

Operators behave like matrices (with some exceptions - see below) but are defined by their effect when applied to a vector. They can be transposed, conjugated, or combined with other operators cheaply. The costly operation is deferred until multiplied with a vector.

... input elements only have a finite number of possible values, for example, PlutoUI.Slider(5:15) can only have 11 values. For finite inputs like the slider, PlutoSliderServer can run the slider server in advance, and precompute the results to all possible inputs (in other words: precompute the response to all possible requests).

LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone.

MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack

Stores your favorites Books. Lets you track the Users logged,signed up. Time tracing of system access. Delete, and Add both Categories and Books. No fussy configurations, embedded database with Java Runtime Environment enabled.