auto-sklearn

Open Source

AutoML Updated Feb 15, 2026

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Compared with 14 other AutoML agents Open source Self-hostable Updated Feb 2026

💰 Open Source 🔄 Updated Feb 2026 🖥️ Self-hostable

💰 Pricing

Open Source

Pricing not publicly listed.

🎯 Use Cases

Automated hyperparameter tuning for scikit-learn models Rapid prototyping of machine learning solutions Benchmarking different ML pipelines Educational purposes for learning AutoML techniques

⚖️ Pros & Cons

✅ Pros

Seamless integration with scikit-learn
Leverages meta-learning for faster optimization
Open-source and community-supported

❌ Cons

Limited to scikit-learn compatible models
Can be computationally expensive for large datasets
Requires some familiarity with scikit-learn

Overview

auto-sklearn is an automated machine learning tool that extends scikit-learn by automatically searching for the best machine learning pipeline, including model selection and hyperparameter tuning. It leverages meta-learning and Bayesian optimization to improve efficiency and performance.

Problem It Solves

It eliminates the need for manual trial-and-error in selecting and tuning machine learning models, saving time and improving model accuracy.

Target Audience: Developers and teams working with automl automation.

Inputs

• User configuration
• API credentials (if required)
• Task parameters

Outputs

• Automated task results
• Status reports
• Generated content or actions

Example Workflow

1 User configures the agent with required parameters
2 Agent receives input data or trigger
3 Agent processes the request using its core logic
4 Agent interacts with external services if needed
5 Results are returned to the user

Sample System Prompt


              You are auto-sklearn, an AI assistant. Help the user accomplish their task efficiently.

Tools & Technologies

LLM APIs Python

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FAQs

Is this agent open-source?: Yes
Can this agent be self-hosted?: Yes
What skill level is required?: Intermediate

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