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Showing 3214 open source projects for "java open source"
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Automate contact and company data extractionGenerate leads at scale without building or maintaining scrapers. Use 10,000+ ready-made tools that handle authentication, pagination, and anti-bot protection. Pull data from business directories, social profiles, and public sources, then export to your CRM or database via API. Schedule recurring extractions, enrich existing datasets, and integrate with your workflows.
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Total Network Visibility for Network Engineers and IT ManagersThis means every device on your network, and every interface on every device is automatically analyzed for performance, errors, QoS, and configuration.
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ArrayFire.jl
Julia wrapper for the ArrayFire library
ArrayFire is a library for GPU and accelerated computing. ArrayFire.jl wraps the ArrayFire library for Julia, and provides a Julia interface. Install ArrayFire library: either download a binary from the official site, or you can build from source. -
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ElectronDisplay.jl
An Electron.jl based figure and table display.
This package provides a display for figures, plots and tables. When you load the package, it will push a new display onto the Julia display stack and from then on it will display any value that can be rendered as png, svg, vega, vega-lite or plotly in an electron-based window. This is especially handy when one works on the REPL and wants plots or tables to show up in a nice window. -
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Reproducible-research
A Reproducible Data Analysis Workflow with R Markdown, Git, Make, etc.
In this tutorial, we describe a workflow to ensure long-term reproducibility of R-based data analyses. The workflow leverages established tools and practices from software engineering. It combines the benefits of various open-source software tools including R Markdown, Git, Make, and Docker, whose interplay ensures seamless integration of version management, dynamic report generation conforming to various journal styles, and full cross-platform and long-term computational reproducibility. The workflow ensures meeting the primary goals that 1) the reporting of statistical results is consistent with the actual statistical results (dynamic report generation), 2) the analysis exactly reproduces at a later point in time even if the computing platform or software is changed (computational reproducibility), and 3) changes at any time (during development and post-publication) are tracked, tagged, and documented while earlier versions of both data and code remain accessible. -
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DISTOD
Distributed discovery of bidirectional order dependencies
The DISTOD data profiling algorithm is a distributed algorithm to discover bidirectional order dependencies (in set-based form) from relational data. DISTOD is based on the single-threaded FASTOD-BID algorithm [1], but DISTOD scales elastically to many machines outperforming FASTOD-BID by up to orders of magnitude. Bidirectional order dependencies (bODs) capture order relationships between lists of attributes in a relational table. They can express that, for example, sorting books by... -
Free and Open Source HR SoftwareGive your HR team the tools they need to streamline administrative tasks, support employees, and make informed decisions with the OrangeHRM free and open source HR software.
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Jupytab
Display in Tableau data from Jupyter notebooks
Jupytab allows you to explore in Tableau data which is generated dynamically by a Jupyter Notebook. You can thus create Tableau data sources in a very flexible way using all the power of Python. This is achieved by having Tableau access data through a web server created by Jupytab. -
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GPlates
Interactive visualization of plate tectonics.
GPlates is a plate-tectonics program. Manipulate reconstructions of geological and paleo-geographic features through geological time. Interactively visualize vector, raster and volume data. PyGPlates is the GPlates Python library. Get fine-grained access to GPlates functionality in your Python scripts. -
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Arexx Data Logger UI
A web UI to Arexx temperature loggers
This project aims at displaying and analysing data recorded by Arexx temperature loggers on Unix operating systems. Although the code is currently implemented for etching data from Arexx loggers, the UI itself is completely independent and can be reused with other temperature databases. -
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InfoPoint
A flexible data management system
InfoPoint is a flexible data management system, intended not only to store data itself but also to provide interfaces to other sources or targets of comparable structured data. -
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eMatrix
A C++ Matrix Library
eMatrix is a lightweight matrix library developed in C++. EMatrix is designed to help solve engineering problems requiring linear algebra. eMatrix is OS independent and is fairly portable. New features include inv(A) and det(A). -
Run applications fast and securely in a fully managed environmentRun frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
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IPyPublish
Workflow for creating and editing publication ready scientific reports
A program for creating and editing publication-ready scientific reports and presentations, from one or more Jupyter Notebooks. Dynamically (and reproducibly) explore data, run code, and output the results. Dynamically edit and visualize the basic components of the document (text, math, figures, tables, references, citations, etc). Have precise control over what elements are output to the final document and how they are layed out and typeset. Also be able to output the same source document to... -
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Limada (Linked Marked Data) is a framework for managing relationships of data in non-hierarchical structures, where the individual elements are interconnected in complex ways. The philosophy behind: Information is connection, is relationship of data.
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JuliaDB.jl
Parallel analytical database in pure Julia
JuliaDB is a package for working with large persistent data set. JuliaDB provides distributed table and array datastructures with convenient functions to load data from CSV. JuliaDB is Julia all the way down. This means queries can be composed with Julia code that may use a vast ecosystem of packages. -
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CNN Explainer
Learning Convolutional Neural Networks with Interactive Visualization
In machine learning, a classifier assigns a class label to a data point. For example, an image classifier produces a class label (e.g, bird, plane) for what objects exist within an image. A convolutional neural network, or CNN for short, is a type of classifier, which excels at solving this problem! A CNN is a neural network: an algorithm used to recognize patterns in data. Neural Networks in general are composed of a collection of neurons that are organized in layers, each with their own... -
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Query.jl
Query almost anything in julia
Query is a package for querying julia data sources. It can filter, project, join and group data from any iterable data source, including all the sources supported in IterableTables.jl. One can for example query any of the following data sources: any array, DataFrames, DataStreams (including CSV, Feather, SQLite, ODBC), DataTables, IndexedTables, TimeSeries, Temporal, TypedTables and DifferentialEquations (any DESolution). The package currently provides working implementations for in-memory... -
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Optimus
Agile Data Preparation Workflows made easy with Pandas
Easily write code to clean, transform, explore and visualize data using Python. Process using a simple API, making it easy to use for newcomers. More than 100 functions to handle strings, process dates, urls and emails. Easily plot data from any size. Out-of-box functions to explore and fix data quality. Use the same code to process your data in your laptop or in a remote cluster of GPUs. -
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ArgCheck.jl
Package for checking function arguments
Package for checking function arguments. @argcheck code is as fast as @assert or a hand written if. That being said it is possible to erase argchecks, much like one can erase bounds checking using @inbounds. This feature is currently experimental. It may be silently changed or removed without increasing the major ArgCheck version number. -
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NLOptControl.jl
nonlinear control optimization tool
This software solves nonlinear control problems at a high level very quickly. -
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repo2docker GitHub Action
A GitHub action to build data science environment images
Trigger repo2docker to build a Jupyter enabled Docker image from your GitHub repository and push this image to a Docker registry of your choice. This will automatically attempt to build an environment from configuration files found in your repository. Images generated by this action are automatically tagged with both latest and <SHA> corresponding to the relevant commit SHA on GitHub. Both tags are pushed to the Docker registry specified by the user. If an existing image with the latest tag... -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than... -
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CUDAnative.jl
Julia support for native CUDA programming
The programming support for NVIDIA GPUs in Julia is provided by the CUDA.jl package. It is built on the CUDA toolkit and aims to be as full-featured and offer the same performance as CUDA C. The toolchain is mature, has been under development since 2014, and can easily be installed on any current version of Julia using the integrated package manager. -
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StellarGraph
Machine Learning on Graphs
StellarGraph is a Python library for machine learning on graphs and networks. The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can... -
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CuArrays.jl
A Curious Cumulation of CUDA Cuisine
CuArrays provides a fully-functional GPU array, which can give significant speedups over normal arrays without code changes. CuArrays are implemented fully in Julia, making the implementation elegant and extremely generic. -
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SageMaker Containers
Create SageMaker-compatible Docker containers
Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. The SageMaker Training Toolkit can be easily added to... -
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Poli
An easy-to-use BI server built for SQL lovers. Power data analysis
An easy-to-use BI server built for SQL lovers. Power data analysis in SQL and gain faster business insights. Platform independent web application. Single JAR file + Single SQLite DB file. Get up and running in 5 minutes. PostgreSQL, Oracle, SQL Server, MySQL, Elasticsearch... You name it. No ETLs, no generated SQL, polish your own SQL query to transform data. Pixel-perfect positioning + Drag'n'Drop support to customize the reports and charts in your own way. Utilize the power of dynamic SQL... -
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immutability-helper
Mutate a copy of data without changing the original source
React lets you use whatever style of data management you want, including mutation. However, if you can use immutable data in performance-critical parts of your application it's easy to implement a fast shouldComponentUpdate() method to significantly speed up your app. Dealing with immutable data in JavaScript is more difficult than in languages designed for it, like Clojure. However, we've provided a simple immutability helper, update(), that makes dealing with this type of data much easier,...
