Showing 4 open source projects for "internal mail system"

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  • 1
    Vearch

    Vearch

    A distributed system for embedding-based vector retrieval

    Vearch is the vector search infrastructure for deep learning and AI applications. Vearch is a distributed vector storage and retrieval system which can be easily extended to billions scale. Vearch implements a high-performance, lockless real-time vector indexing subsystem that utilizes various optimization techniques to support millisecond vector update and retrieval. End-to-end one-click deployment. Through the module of the plugin, a complete default visual search system can be deployed just with one click. ...
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  • 2
    Netflix Maestro

    Netflix Maestro

    Netflix’s Workflow Orchestrator

    Maestro is a large-scale workflow orchestration platform originally developed by Netflix to coordinate complex data processing and machine learning workflows across distributed systems. The system acts as a general-purpose workflow orchestrator that manages the execution, scheduling, monitoring, and recovery of large pipelines used for analytics and AI operations. It was designed to support the demanding internal infrastructure of Netflix, where thousands of workflows must process massive volumes of data reliably and efficiently every day. ...
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  • 3
    MTBook

    MTBook

    Machine Translation: Foundations and Models

    ...This book is divided into four parts, each of which consists of several chapters. The order of the chapters refers to the time context of the development of machine translation technology, while taking into account the internal logic of the machine translation knowledge system.
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  • 4
    spark-ml-source-analysis

    spark-ml-source-analysis

    Spark ml algorithm principle analysis and specific source code

    spark-ml-source-analysis is a technical repository that analyzes the internal implementation of machine learning algorithms within Apache Spark’s MLlib library. The project aims to help developers and data scientists understand how distributed machine learning algorithms are implemented and optimized inside the Spark ecosystem. Instead of providing a runnable software system, the repository focuses on explaining algorithm principles and examining the underlying source code used in Spark’s machine learning package. ...
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