5 projects for "code-server" with 2 filters applied:

  • Catch Bugs Before Your Customers Do Icon
    Catch Bugs Before Your Customers Do

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    Move from alert to fix before users notice. AppSignal monitors errors, performance bottlenecks, host health, and uptime—all from one dashboard. Instant notifications on deployments, anomaly triggers for memory spikes or error surges, and seamless log management. Works out of the box with Rails, Django, Express, Phoenix, Next.js, and dozens more. Starts at $23/month with no hidden fees.
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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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  • 1
    NVIDIA Merlin

    NVIDIA Merlin

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

    ...Scale large deep learning recommender models by distributing large embedding tables that exceed available GPU and CPU memory. Deploy data transformations and trained models to production with only a few lines of code.
    Downloads: 0 This Week
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  • 2
    AWS SDK for pandas

    AWS SDK for pandas

    Easy integration with Athena, Glue, Redshift, Timestream, Neptune

    aws-sdk-pandas (formerly AWS Data Wrangler) bridges pandas with the AWS analytics stack so DataFrames flow seamlessly to and from cloud services. With a few lines of code, you can read from and write to Amazon S3 in Parquet/CSV/JSON/ORC, register tables in the AWS Glue Data Catalog, and query with Amazon Athena directly into pandas. The library abstracts efficient patterns like partitioning, compression, and vectorized I/O so you get performant data lake operations without hand-rolling boilerplate. ...
    Downloads: 0 This Week
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  • 3
    CSAPP-Labs

    CSAPP-Labs

    Solutions and Notes for Labs of Computer Systems

    ...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 experiments. Each lab is structured to include test programs, Makefiles, harnesses, and step-by-step instructions that guide students through hands-on interaction with low-level programming and system behavior. By actually building and debugging code that runs close to hardware, learners acquire intuition about performance trade-offs, bit-level manipulation, stack frame layout, and how compilers and OS features influence execution.
    Downloads: 5 This Week
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  • 4
    Data Science Notes

    Data Science Notes

    Curated collection of data science learning materials

    Data Science Notes is a large, curated collection of data science learning materials, with explanations, code snippets, and structured notes across the typical end-to-end workflow. It spans foundational math and statistics through data wrangling, visualization, machine learning, and practical project organization. The content emphasizes hands-on understanding by pairing narrative notes with runnable examples, making it useful for both self-study and classroom settings.
    Downloads: 0 This Week
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  • $300 in Free Credit Across 150+ Cloud Services Icon
    $300 in Free Credit Across 150+ Cloud Services

    VMs, containers, AI, databases, storage | build anything. No commitment to start.

    Start your project in minutes. After credits run out, 20+ products include free monthly usage. Only pay when you're ready to scale with Google Cloud.
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  • 5
    Data Science Specialization

    Data Science Specialization

    Course materials for the Data Science Specialization on Coursera

    The Data Science Specialization Courses repository is a collection of materials that support the Johns Hopkins University Data Science Specialization on Coursera. It contains the source code and resources used throughout the specialization’s courses, covering a broad range of data science concepts and techniques. The repository is designed as a shared space for code examples, datasets, and instructional materials, helping learners follow along with lectures and assignments. It spans essential topics such as R programming, data cleaning, exploratory data analysis, statistical inference, regression models, machine learning, and practical data science projects. ...
    Downloads: 2 This Week
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