Showing 5 open source projects for "python q learning"

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  • Desktop and Mobile Device Management Software Icon
    Desktop and Mobile Device Management Software

    It's a modern take on desktop management that can be scaled as per organizational needs.

    Desktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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  • DialedIn: Cloud Contact Center Software Icon
    DialedIn: Cloud Contact Center Software

    Cloud Based Contact Center Software that Drives Success

    DialedIn is a modern call center software designed to transform customer interactions and streamline your operations, helping teams achieve more daily. By automating and optimizing key workflows across inbound, outbound, and blended environments, DialedIn helps you boost agent productivity and deliver better outcomes across every call.
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  • 1
    Kubeflow Training Operator

    Kubeflow Training Operator

    Distributed ML Training and Fine-Tuning on Kubernetes

    Kubeflow Training Operator is a Kubernetes-native project for fine-tuning and scalable distributed training of machine learning (ML) models created with various ML frameworks such as PyTorch, TensorFlow, XGBoost, MPI, Paddle, and others.
    Downloads: 2 This Week
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  • 2
    Katib

    Katib

    Automated Machine Learning on Kubernetes

    Katib is a Kubernetes-native project for automated machine learning (AutoML). Katib supports Hyperparameter Tuning, Early Stopping and Neural Architecture Search. Katib is a project that is agnostic to machine learning (ML) frameworks. It can tune hyperparameters of applications written in any language of the users’ choice and natively supports many ML frameworks, such as TensorFlow, Apache MXNet, PyTorch, XGBoost, and others. Katib can perform training jobs using any Kubernetes Custom...
    Downloads: 0 This Week
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  • 3
    aqueduct LLM

    aqueduct LLM

    Aqueduct allows you to run LLM and ML workloads on any infrastructure

    Aqueduct is an MLOps framework that allows you to define and deploy machine learning and LLM workloads on any cloud infrastructure. Aqueduct is an open-source MLOps framework that allows you to write code in vanilla Python, run that code on any cloud infrastructure you'd like to use, and gain visibility into the execution and performance of your models and predictions. Aqueduct's Python native API allows you to define ML tasks in regular Python code. ...
    Downloads: 0 This Week
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  • 4
    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
    Downloads: 0 This Week
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  • Build Your Live Streaming Platform Icon
    Build Your Live Streaming Platform

    Scalable, Ultra Low Latency and Adaptive WebRTC Streaming

    Ant Media Server is a streaming engine software that provides adaptive, ultra low latency streaming by using WebRTC technology with ~0.5 seconds latency.
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  • 5
    The Google Cloud Developer's Cheat Sheet

    The Google Cloud Developer's Cheat Sheet

    Cheat sheet for Google Cloud developers

    Every product in the Google Cloud family described in <=4 words (with liberal use of hyphens and slashes) by the Google Developer Relations Team. This list only includes products that are publicly available. There are several products in pre-release/private-alpha that will not be included until they go public beta or GA. Many of these products have a free tier. There is also a free trial that will enable you try almost everything. API platforms and ecosystems, developer and management tools,...
    Downloads: 0 This Week
    Last Update:
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