Alternatives
Self-hosted alternatives to Amazon SageMaker Training
Projects in the registry that can run on your own hardware and serve at least one of the same use cases as Amazon SageMaker Training.
- Source
- Registry relations over fetched repository records — the evidence sits on each repository page
- Verified
- Evidence not verified
- Confidence
- High
01How this list was built
- Compared against
- Amazon SageMaker Training
- Delivery
- Cloud platforms
- Shared use cases
- Prediction from operational data, Choosing a cloud platform
- Selection rule
- open source, or self-hostable, and shares a use case
- Candidates found
- 3
02Alternatives
MLflow
Cloud platforms
Experiment tracking, a model registry and deployment packaging. The component that lets a prediction be traced back to the model version and data that produced it.
- Repository
- mlflow/mlflow
- Stars
- —
- Licence
- unknown
- In stacks
- 1
Shares: Predictive analytics
scikit-learn
Libraries
The standard Python library for classical machine learning: regression, classification, clustering, preprocessing pipelines and model evaluation on tabular data.
- Repository
- scikit-learn/scikit-learn
- Stars
- —
- Licence
- unknown
- In stacks
- 1
Shares: Predictive analytics
XGBoost
Libraries
Gradient-boosted decision trees with distributed training and GPU support. The usual first model to try on a tabular prediction problem before anything more elaborate.
- Repository
- dmlc/xgboost
- Stars
- —
- Licence
- unknown
- In stacks
- 1
Shares: Predictive analytics
03Repository facts
| Repository | Stars | Health |
|---|---|---|
| mlflow/mlflow | — | Health not measuredunknown |
| scikit-learn/scikit-learn | — | Health not measuredunknown |
| dmlc/xgboost | — | Health not measuredunknown |
04Ask about your own case
Which alternative is right depends on how many people will use it, what the data is and what you can operate. Ask and the answer is researched for your organisation.