Automate machine learning workflows from data profiling to deployment.
npx skills add https://github.com/GiacomoSaccaggi/scomp_link --skill scomp-link
Please help me install this Agent Skill. Skill: scomp-link Source: https://github.com/GiacomoSaccaggi/scomp_link/tree/main/skills/scomp-link Command: npx skills add https://github.com/GiacomoSaccaggi/scomp_link --skill scomp-link
This Skill solves the fragmentation of machine learning workflows by providing a unified, zero-code toolkit that handles everything from initial data profiling to production deployment.
Use the scomp-link skill to profile the dataset named train.csv and generate a summary table.
High-intent search queries and answers about installing and using this skill.
You can automate machine learning workflows from the command line by using a zero-code toolkit that handles end-to-end pipelines, including data profiling, feature engineering, model training, and deployment.
The best way to train a scikit-learn model with automated hyperparameter tuning and serve it as a REST API is to use an end-to-end automation pipeline that generates production-ready artifacts and deploys them directly via Flask.
Yes, you need pandas and numpy installed to execute automated data profiling and feature engineering pipelines, as these libraries are required dependencies for processing data and generating persistent model artifacts.
You can version and persist trained machine learning models and preprocessors by generating persistent .scomp artifacts that contain models, preprocessing logic, and evaluation metrics for reliable production monitoring.
Optuna integrates with automated model selection for predictive modeling by providing automated hyperparameter tuning capabilities within the end-to-end machine learning workflow, optimizing scikit-learn models during the training pipeline.
omicverseClean, reshape, normalize and engineer features from CSV/TSV/Parquet inputs using pandas and numpy locally.
seb1nDeploy trained machine learning models via REST APIs, Docker, and Kubernetes.
itallstartedwithaideaBuild reproducible PyTorch and scikit-learn pipelines with stratified cross-validation and Optuna tuning.
brahiamsinhoOrchestrate multi-agent ML pipelines across data engineering, model training, deployment, and monitoring.
