Open Source Julia Algorithms
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Julia Algorithms
View 5732 business solutionsBrowse free open source Julia Algorithms and projects below. Use the toggles on the left to filter open source Julia Algorithms by OS, license, language, programming language, and project status.
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Monitor your whole IT InfrastructureCaters to tech staff, system Administrators, and companies of any size, from small and medium sized businesses to enterprises that need their IT network to be reliable and easy to monitor in real-time. Equipped with an easy-to-use, intuitive interface with a cutting-edge monitoring engine. PRTG optimizes connections and workloads as well as reducing operational costs by avoiding outages while saving time and controlling service level agreements (SLAs).
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The only CRM built for B2CKlaviyo unifies your customer profiles by capturing every event, and then lets you orchestrate your email marketing, SMS marketing, push notifications, WhatsApp, and RCS campaigns in one place. Klaviyo AI helps you build audiences, write copy, and optimize — so you can always send the right message at the right time, automatically. With real-time attribution and insights, you'll be able to make smarter, faster decisions that drive ROI.
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AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero
Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++) and optimized for highly distributed computing environments. This makes them hardly accessible for students, researchers and hackers. Many simple Python implementations can be found on Github, but none of them is able to beat a reasonable baseline on games such as Othello or Connect Four. As an illustration, the benchmark in the README of the most popular of them only features a random baseline, along with a greedy baseline that does not appear to be significantly stronger. -
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DecisionTree.jl
Julia implementation of Decision Tree (CART) Random Forest algorithm
Julia implementation of Decision Tree (CART) and Random Forest algorithms. -
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Evolutionary.jl
Evolutionary & genetic algorithms for Julia
A Julia package for evolutionary & genetic algorithms. The package can be installed with the Julia package manager. -
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Interpolations.jl
Fast, continuous interpolation of discrete datasets in Julia
This package implements a variety of interpolation schemes for the Julia language. It has the goals of ease of use, broad algorithmic support, and exceptional performance. Currently, this package supports B-splines and irregular grids. The API has been designed with the intent to support more options. Initial support for Lanczos interpolation was recently added. Pull requests are more than welcome! It should be noted that the API may continue to evolve over time. -
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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
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