Showing 9 open source projects for "queue management systems"

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  • 1
    ggplot2

    ggplot2

    An implementation of the Grammar of Graphics in R

    ggplot2 is a system written in R for declaratively creating graphics. It is based on The Grammar of Graphics, which focuses on following a layered approach to describe and construct visualizations or graphics in a structured manner. With ggplot2 you simply provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it will take care of the rest. ggplot2 is over 10 years old and is used by hundreds of thousands of people all over the world for...
    Downloads: 21 This Week
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  • 2
    XGBoost

    XGBoost

    Scalable and Flexible Gradient Boosting

    XGBoost is an optimized distributed gradient boosting library, designed to be scalable, flexible, portable and highly efficient. It supports regression, classification, ranking and user defined objectives, and runs on all major operating systems and cloud platforms. XGBoost works by implementing machine learning algorithms under the Gradient Boosting framework. It also offers parallel tree boosting (GBDT, GBRT or GBM) that can quickly and accurately solve many data science problems....
    Downloads: 7 This Week
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  • 3
    RStudio

    RStudio

    RStudio is an integrated development environment (IDE) for R

    RStudio is a powerful, full-featured integrated development environment (IDE) tailored primarily for the R programming language but increasingly supportive of other languages like Python and Julia. It brings together console, editor, plotting, workspace, history, and file-management panes into a unified interface, helping data scientists, statisticians, and analysts to work more productively. The IDE is cross-platform: there are desktop versions for Windows, macOS and Linux, as well as a server version for remote or multi-user deployment via a web browser. In addition to code editing and execution, RStudio offers extensive support for reproducible research via R Markdown, notebooks, and integration with version control systems like Git and SVN. ...
    Downloads: 10 This Week
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  • 4
    Great Expectations

    Great Expectations

    Always know what to expect from your data

    Great Expectations helps data teams eliminate pipeline debt, through data testing, documentation, and profiling. Software developers have long known that testing and documentation are essential for managing complex codebases. Great Expectations brings the same confidence, integrity, and acceleration to data science and data engineering teams. Expectations are assertions for data. They are the workhorse abstraction in Great Expectations, covering all kinds of common data issues. Expectations...
    Downloads: 2 This Week
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  • 5
    sadsa

    sadsa

    SADSA (Software Application for Data Science and Analytics)

    SADSA (Software Application for Data Science and Analytics) is a Python-based desktop application designed to simplify statistical analysis, machine learning, and data visualization for students, researchers, and data professionals. Built using Python for the GUI, SADSA provides a menu-driven interface for handling datasets, applying transformations, running advanced statistical tests, machine learning algorithms, and generating insightful plots — all without writing code.
    Downloads: 0 This Week
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  • 6
    NVIDIA Merlin

    NVIDIA Merlin

    Library providing end-to-end GPU-accelerated recommender systems

    NVIDIA Merlin is an open-source library that accelerates recommender systems on NVIDIA GPUs. The library enables data scientists, machine learning engineers, and researchers to build high-performing recommenders at scale. Merlin includes tools to address common feature engineering, training, and inference challenges. Each stage of the Merlin pipeline is optimized to support hundreds of terabytes of data, which is all accessible through easy-to-use APIs. For more information, see NVIDIA...
    Downloads: 2 This Week
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  • 7
    CSAPP-Labs

    CSAPP-Labs

    Solutions and Notes for Labs of Computer Systems

    CSAPP-Labs is a repository that organizes and provides practical lab exercises corresponding to the famous textbook Computer Systems: A Programmer’s Perspective (CS:APP), helping students deepen their understanding of how computer systems work at the machine level. The exercises cover core topics such as data representation, assembly language, processor architecture, cache behavior, memory hierarchy, linking, and concurrency, contextualizing abstract concepts from the book in real code and...
    Downloads: 4 This Week
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  • 8
    Self-learning-Computer-Science

    Self-learning-Computer-Science

    Resources to learn computer science in your spare time

    Self-learning Computer Science is a curated, open-source guide repository designed to help learners independently study computer science topics using high-quality university-level resources. The author (an undergraduate CS student) assembled links to courses from institutions like MIT, UC Berkeley, Stanford, etc., covering mathematics, programming, data structures/algorithms, computer architecture, machine learning, software engineering and more. It’s aimed at learners who find traditional...
    Downloads: 0 This Week
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  • 9
    Amazon SageMaker Examples

    Amazon SageMaker Examples

    Jupyter notebooks that demonstrate how to build models using SageMaker

    Welcome to Amazon SageMaker. This projects highlights example Jupyter notebooks for a variety of machine learning use cases that you can run in SageMaker. If you’re new to SageMaker we recommend starting with more feature-rich SageMaker Studio. It uses the familiar JupyterLab interface and has seamless integration with a variety of deep learning and data science environments and scalable compute resources for training, inference, and other ML operations. Studio offers teams and companies...
    Downloads: 0 This Week
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