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2 مستودعات

Awesome GitHub RepositoriesContainerized Training

Packaging custom algorithms and frameworks into containers for execution on managed infrastructure.

Distinct from Model Training Frameworks: Distinct from general frameworks by focusing specifically on the containerization and deployment of the training environment.

Explore 2 awesome GitHub repositories matching artificial intelligence & ml · Containerized Training. Refine with filters or upvote what's useful.

Awesome Containerized Training GitHub Repositories

اعثر على أفضل المستودعات باستخدام الذكاء الاصطناعي.سنبحث عن أفضل المستودعات المطابقة باستخدام الذكاء الاصطناعي.
  • aws/amazon-sagemaker-examplesالصورة الرمزية لـ aws

    aws/amazon-sagemaker-examples

    10,958عرض على GitHub↗

    This repository is a collection of Jupyter notebooks providing reference implementations and templates for building, training, and deploying machine learning models using Amazon SageMaker. It serves as an example library for implementing model architectures and automating the machine learning lifecycle. The library provides practical patterns for machine learning training, data engineering, and model deployment. It includes implementation guides for MLOps, including workflows for model monitoring, lineage tracking, and hyperparameter tuning. The examples cover a broad range of capabilities i

    Provides templates for packaging custom ML algorithms into Docker containers for managed training.

    Jupyter Notebookawsdata-sciencedeep-learning
    عرض على GitHub↗10,958
  • polyaxon/polyaxonالصورة الرمزية لـ polyaxon

    polyaxon/polyaxon

    3,707عرض على GitHub↗

    Polyaxon is a Kubernetes-native machine learning orchestration platform and MLOps pipeline orchestrator. It serves as a control plane for managing distributed deep learning workloads, automated machine learning pipelines, and experiment tracking. The platform distinguishes itself through specialized services for distributed training management, including MPI-based coordination for PyTorch and TensorFlow. It provides an automated hyperparameter optimization service utilizing Bayesian, random, and grid search algorithms, alongside managed interactive AI workspaces for launching Jupyter notebook

    Executes data processing and training tasks in containerized environments to ensure consistent and reproducible runtimes.

    MDX
    عرض على GitHub↗3,707
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