80 projects for "stack" with 2 filters applied:

  • Host LLMs in Production With On-Demand GPUs Icon
    Host LLMs in Production With On-Demand GPUs

    NVIDIA L4 GPUs. 5-second cold starts. Scale to zero when idle.

    Deploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

    Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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  • 1
    Data Science and Machine Learning Career

    Data Science and Machine Learning Career

    Career Resources for Data Science, Machine Learning and Big Data

    ...Community groups and professional networks help readers find peers and industry discussions. Its broad structure supports both early exploration and practical job-search preparation. Rather than teaching one technical stack, it acts as a navigation guide across education, hiring, professional development, and career research.
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  • 2
    PyCls

    PyCls

    Codebase for Image Classification Research, written in PyTorch

    ...Model definitions are concise and modular, making it easy to prototype new blocks or swap backbones while keeping the rest of the pipeline unchanged. Pretrained weights and evaluation scripts cover common datasets, and the logging/metric stack is designed for quick comparison across runs. Practitioners use pycls both as a baseline factory and as a scaffold for new classification backbones.
    Downloads: 0 This Week
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  • 3
    Learn_Data_Science_in_3_Months

    Learn_Data_Science_in_3_Months

    This is the Curriculum for "Learn Data Science in 3 Months"

    This project lays out a 12-week plan to go from basics to a portfolio-ready understanding of data science. It breaks the journey into clear stages: Python fundamentals, data wrangling, visualization, statistics, machine learning, and end-to-end projects. The schedule mixes learning and doing, encouraging you to build small deliverables each week—like notebooks, dashboards, and model demos—to reinforce skills. It also includes suggestions for datasets and problem domains so you aren’t stuck...
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  • 4
    Mellum-4b-base

    Mellum-4b-base

    JetBrains’ 4B parameter code model for completions

    ...Built with 4 billion parameters and a LLaMA-style architecture, it was trained on over 4.2 trillion tokens across multiple programming languages, including datasets such as The Stack, StarCoder, and CommitPack. With a context window of 8,192 tokens, it excels at code completion, fill-in-the-middle tasks, and intelligent code suggestions for professional developer tools and IDEs. The model is efficient for both cloud inference with vLLM and local deployment using llama.cpp or Ollama, thanks to its bf16 precision and AMP training. ...
    Downloads: 0 This Week
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  • $300 Free Credits to Build on Google Cloud Icon
    $300 Free Credits to Build on Google Cloud

    New customers can spin up VMs, build with AI, and query data at no cost.

    Put your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
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  • 5
    Kimi K2.6

    Kimi K2.6

    Multimodal agent model for coding, orchestration, and autonomy

    ...It is designed to handle complex end-to-end software workflows across multiple languages and domains, including front-end development, DevOps, performance optimization, and coding-driven design. Beyond coding, it can transform prompts and visual inputs into production-ready interfaces and lightweight full-stack outputs with structured layouts, interactivity, and polished visual detail. One of its most distinctive capabilities is horizontal agent scaling, supporting up to 300 sub-agents and 4,000 coordinated steps in a single run, which enables parallel task decomposition and end-to-end completion of outputs such as documents, websites, and spreadsheets. ...
    Downloads: 0 This Week
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