Showing 6 open source projects for "open java projects"

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  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

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  • 1
    Metaflow

    Metaflow

    A framework for real-life data science

    Metaflow is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning.
    Downloads: 0 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: 30 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...
    Downloads: 15 This Week
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  • 4
    FlexiList.

    FlexiList.

    FlexiList is a Java data structure that combines the benefits of array

    FlexiList is a Java data structure that combines the benefits of arrays and linked lists. Like an array, it allows for efficient access to elements by index. Like a linked list, it allows for efficient insertion and deletion of elements at any position in the list. Benefits Over Arrays and ArrayList ->Efficient Insertion and Deletion: FlexiList can insert or delete nodes at any position in the list in O(1) time, whereas arrays require shifting all elements after the insertion or deletion...
    Downloads: 0 This Week
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  • Custom VMs From 1 to 96 vCPUs With 99.95% Uptime Icon
    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

    General-purpose, compute-optimized, or GPU/TPU-accelerated. Built to your exact specs.

    Live migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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  • 5
    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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  • 6
    Seldon Server

    Seldon Server

    Machine learning platform and recommendation engine on Kubernetes

    Seldon Server is a machine learning platform and recommendation engine built on Kubernetes. Seldon reduces time-to-value so models can get to work faster. Scale with confidence and minimize risk through interpretable results and transparent model performance. Seldon Core focuses purely on deploying a wide range of ML models on Kubernetes, allowing complex runtime serving graphs to be managed in production. Seldon Core is a progression of the goals of the Seldon-Server project but also a more...
    Downloads: 0 This Week
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