moheetsubudhi-isb/ml-toolkit
v1.0.0MIT
Data-science skills for framing ML problems, auditing data, engineering features, reducing dimensions, clustering, model selection and validation, classification and regression metrics, tree ensembles, linear and logistic models, anomaly detection, and text embeddings.
What this package declares
The file a client reads when it loads this plugin, exactly as this revision carries it.
plugin.json
{
"$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json",
"name": "ml-toolkit",
"version": "1.0.0",
"description": "Data-science skills for framing ML problems, auditing data, engineering features, reducing dimensions, clustering, model selection and validation, classification and regression metrics, tree ensembles, linear and logistic models, anomaly detection, and text embeddings.",
"author": {
"name": "Moheet Subudhi"
},
"homepage": "https://github.com/moheetsubudhi-isb/business-analytics-skills",
"repository": "https://github.com/moheetsubudhi-isb/business-analytics-skills",
"license": "MIT",
"keywords": [
"analytics",
"decision-support",
"ml"
],
"extensions": {
"com.openai": {
"interface": {
"displayName": "Ml toolkit",
"shortDescription": "Data-science skills for framing ML problems, auditing data, engineering features, reducing dimensions, clustering,\u2026",
"longDescription": "Data-science skills for framing ML problems, auditing data, engineering features, reducing dimensions, clustering, model selection and validation, classification and regression metrics, tree ensembles, linear and logistic models, anomaly detection, and text embeddings.",
"developerName": "Moheet Subudhi",
"category": "Productivity"
}
}
}
}
What else this package ships
These files come with the package and this site does not publish them. They are listed so you know what is there before you install it.
- 10Python files
Client extensions
Data this package carries for particular clients. The directory lists the clients named and never reads what is addressed to them.
- com.openai