Does this skill support both classification and regression?

Yes, it can handle various machine learning tasks including classification, regression, and general automated model building based on your specific data requirements.

Can I integrate this with other Claude Code plugins?

Absolutely. It is designed to work alongside data visualization, processing, and deployment plugins to create a complete end-to-end machine learning ecosystem.

What does the AutoML Pipeline Builder skill do?

It automates the process of building, training, and evaluating machine learning models by generating code for feature engineering, model selection, and hyperparameter tuning.

How does it handle data validation?

The skill automatically incorporates data validation and error handling techniques into the generated code to ensure the pipeline runs smoothly and handles unexpected data issues.

What information does the skill provide after execution?

After building the pipeline, the skill provides performance metrics, insights into the model's behavior, and documentation for the saved artifacts.

AutoML Pipeline Builder

Name: AutoML Pipeline Builder
Author: jeremylongshore

byjeremylongshore

•

883

データサイエンスとML

Automates the end-to-end creation of machine learning pipelines including feature engineering, model selection, and hyperparameter tuning.

概要

This skill empowers Claude to streamline the machine learning lifecycle by leveraging the automl-pipeline-builder plugin to generate production-ready code. It automates complex tasks such as data preprocessing, model selection, and optimization, making it an essential tool for developers and data scientists who need to build robust ML workflows quickly. By incorporating built-in data validation and performance metrics, it ensures that generated pipelines are both efficient and reliable for tasks like classification and regression.

主な機能

Comprehensive performance metrics and artifact documentation
Built-in data validation and robust error handling
Automated model selection and hyperparameter optimization
Streamlined feature engineering and data preprocessing
Seamless integration with data visualization and deployment tools
883 GitHub stars

ユースケース

Rapidly prototyping end-to-end machine learning workflows for new datasets
Building customer churn classification models with automated tuning
Creating regression pipelines for predictive analytics like house price forecasting

概要

主な機能

Comprehensive performance metrics and artifact documentation
Built-in data validation and robust error handling
Automated model selection and hyperparameter optimization
Streamlined feature engineering and data preprocessing
Seamless integration with data visualization and deployment tools
883 GitHub stars

ユースケース

Rapidly prototyping end-to-end machine learning workflows for new datasets
Building customer churn classification models with automated tuning
Creating regression pipelines for predictive analytics like house price forecasting