2 repository-uri
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
Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
- aws/amazon-sagemaker-examples
aws/amazon-sagemaker-examples
10,958Vezi pe GitHubThis 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 - polyaxon/polyaxon
polyaxon/polyaxon
3,707Vezi pe GitHubPolyaxon 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.
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