Search

PythonReactSEOPDF
GitHub Skill

ml-integration-patterns

Machine learning integration patterns for rRNA-Phylo covering three use cases - rRNA sequence classification (supervised learning with sklearn/PyTorch), multi-tree consensus (ensemble methods), and generative tree synthesis (GNNs/transformers). Includes feature engineering, model training, hyperparameter tuning, model serving, versioning, and evaluation metrics for bioinformatics ML workflows.

roeimed0☆ 0 Repository stars0 Repository forks

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

View source ↗Guides

Skill instructions

Features and purpose

Machine learning integration patterns for rRNA-Phylo covering three use cases - rRNA sequence classification (supervised learning with sklearn/PyTorch), multi-tree consensus (ensemble methods), and generative tree synthesis (GNNs/transformers). Includes feature engineering, model training, hyperparameter tuning, model serving, versioning, and evaluation metrics for bioinformatics ML workflows.

Quick start

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

Guides ↗

Examples

Read the usage examples in the source repository.

View source ↗

Source history

Indexed on
2026-01-20
Index updated
2026-01-26
Branch
main

Index and sync dates describe this directory. View the source repository for code history.

GitHub ↗

chat Comments (0)

chat_bubble_outline

No comments yet. Be the first to share your thoughts!