The climin package provides optimization methods focused on machine learning scenarios in Python.
Open source
24 alternativesParris
Parris, the automated infrastructure setup tool for machine learning algorithms.
About Parris
Parris is a tool for automating infrastructure setup and training of machine learning algorithms. It launches training stacks so users do not need to SSH into instances to set up servers or monitor progress.
Use requires an AWS account with credentials configured on the workstation, a machine learning algorithm, a dataset to train on, and storage such as an S3 bucket for training results. Installation uses git clone, Python virtualenv, and pip install on Linux or Windows.
Key features
- Automates infrastructure setup for machine learning training jobs
- Launches ML training stacks without SSH into instances
- Uses AWS credentials configured on workstation for provisioning
- Stores training results in S3 bucket or other storage location
- Supports setup on Linux and Windows via Python virtualenv
- Provides configuration options for training stacks
Best for: People who train machine learning algorithms and want to avoid manual server setup and SSH monitoring.
Good for
- Avoids SSH into instances to run training jobs
- Includes Getting Started and Configuration guides for launching stacks
Watch out for
- Requires AWS account with credentials configured via aws configure
- Requires user-supplied algorithm, dataset, and result storage location
Parris at a glance
- Website
- github.com/jgreenemi/Parris
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Platforms
- Linux, Windows
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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