Showing 10 open source projects for "artificial intelligence java source code"

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  • Skillfully - The future of skills based hiring Icon
    Skillfully - The future of skills based hiring

    Realistic Workplace Simulations that Show Applicant Skills in Action

    Skillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
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  • The AI workplace management platform Icon
    The AI workplace management platform

    Plan smart spaces, connect teams, manage assets, and get insights with the leading AI-powered operating system for the built world.

    By combining AI workflows, predictive intelligence, and automated insights, OfficeSpace gives leaders a complete view of how their spaces are used and how people work. Facilities, IT, HR, and Real Estate teams use OfficeSpace to optimize space utilization, enhance employee experience, and reduce portfolio costs with precision.
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  • 1
    ClearML

    ClearML

    Streamline your ML workflow

    ClearML is an open source platform that automates and simplifies developing and managing machine learning solutions for thousands of data science teams all over the world. It is designed as an end-to-end MLOps suite allowing you to focus on developing your ML code & automation, while ClearML ensures your work is reproducible and scalable. The ClearML Python Package for integrating ClearML into your existing scripts by adding just two lines of code, and optionally extending your experiments...
    Downloads: 0 This Week
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  • 2
    marimo

    marimo

    A reactive notebook for Python

    marimo is an open-source reactive notebook for Python, reproducible, git-friendly, executable as a script, and shareable as an app. marimo notebooks are reproducible, extremely interactive, designed for collaboration (git-friendly!), deployable as scripts or apps, and fit for modern Pythonista. Run one cell and marimo reacts by automatically running affected cells, eliminating the error-prone chore of managing the notebook state. marimo's reactive UI elements, like data frame GUIs and plots,...
    Downloads: 2 This Week
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  • 3
    SageMaker Training Toolkit

    SageMaker Training Toolkit

    Train machine learning models within Docker containers

    Train machine learning models within a Docker container using Amazon SageMaker. 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...
    Downloads: 1 This Week
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  • 4
    Quadratic

    Quadratic

    Data science spreadsheet with Python & SQL

    Quadratic enables your team to work together on data analysis to deliver better results, faster. You already know how to use a spreadsheet, but you’ve never had this much power before. Quadratic is a Web-based spreadsheet application that runs in the browser and as a native app (via Electron). Our goal is to build a spreadsheet that enables you to pull your data from its source (SaaS, Database, CSV, API, etc) and then work with that data using the most popular data science tools today...
    Downloads: 6 This Week
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  • Field Service+ for MS Dynamics 365 & Salesforce Icon
    Field Service+ for MS Dynamics 365 & Salesforce

    Empower your field service with mobility and reliability

    Resco’s mobile solution streamlines your field service operations with offline work, fast data sync, and powerful tools for frontline workers, all natively integrated into Dynamics 365 and Salesforce.
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  • 5
    Recommenders

    Recommenders

    Best practices on recommendation systems

    The Recommenders repository provides examples and best practices for building recommendation systems, provided as Jupyter notebooks. The module reco_utils contains functions to simplify common tasks used when developing and evaluating recommender systems. Several utilities are provided in reco_utils to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several...
    Downloads: 0 This Week
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  • 6
    TensorFlow.NET

    TensorFlow.NET

    .NET Standard bindings for Google's TensorFlow for developing models

    TensorFlow.NET (TF.NET) provides a .NET Standard binding for TensorFlow. It aims to implement the complete Tensorflow API in C# which allows .NET developers to develop, train and deploy Machine Learning models with the cross-platform .NET Standard framework. TensorFlow.NET has built-in Keras high-level interface and is released as an independent package TensorFlow.Keras. SciSharp STACK's mission is to bring popular data science technology into the .NET world and to provide .NET developers...
    Downloads: 0 This Week
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  • 7
    SageMaker Inference Toolkit

    SageMaker Inference Toolkit

    Serve machine learning models within a Docker container

    Serve machine learning models within a Docker container using Amazon SageMaker. 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. Once you have a trained model, you can include it in a Docker container that runs your inference code. A container provides an effectively isolated environment, ensuring a consistent runtime regardless of where the...
    Downloads: 0 This Week
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  • 8
    ML workspace

    ML workspace

    All-in-one web-based IDE specialized for machine learning

    All-in-one web-based development environment for machine learning. The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard)...
    Downloads: 0 This Week
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  • 9
    DSTK - Data Science TooKit 3

    DSTK - Data Science TooKit 3

    Data and Text Mining Software for Everyone

    DSTK - Data Science Toolkit 3 is a set of data and text mining softwares, following the CRISP DM model. DSTK offers data understanding using statistical and text analysis, data preparation using normalization and text processing, modeling and evaluation for machine learning and algorithms. It is based on the old version DSTK at https://sourceforge.net/projects/dstk2/ DSTK Engine is like R. DSTK ScriptWriter offers GUI to write DSTK script. DSTK Studio offers SPSS Statistics like GUI...
    Downloads: 0 This Week
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  • Failed Payment Recovery for Subscription Businesses Icon
    Failed Payment Recovery for Subscription Businesses

    For subscription companies searching for a failed payment recovery solution to grow revenue, and retain customers.

    FlexPay’s innovative platform uses multiple technologies to achieve the highest number of retained customers, resulting in reduced involuntary churn, longer life span after recovery, and higher revenue. Leading brands like LegalZoom, Hooked on Phonics, and ClinicSense trust FlexPay to recover failed payments, reduce churn, and increase customer lifetime value.
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  • 10
    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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