sap-hana-ml
v2.4.1SAP HANA Machine Learning Python Client (hana-ml) development skill. Use when: Building ML solutions with SAP HANA's in-database machine learning using Python hana-ml library for PAL/APL algorithms, DataFrame operations, AutoML, model persistence, and visualization. Keywords: hana-ml, SAP HANA, machine learning, PAL, APL, predictive analytics, HANA DataFrame, ConnectionContext, classification, regression, clustering, time series, ARIMA, gradient boosting, AutoML, SHAP, model storage
by Eduard JiglauGPL-3.0404updated 1 day ago
Source
git clone https://github.com/secondsky/sap-skillsClone the source, then follow the repository's marketplace instructions for your runtime. The plugin root is plugins/sap-hana-ml/ inside the repository.
Layout
├── .codex-plugin/plugin.json├── .claude-plugin/plugin.json└── skills/sap-hana-ml/SKILL.md
Skills1
SAP HANA Machine Learning Python Client (hana-ml) development skill. Use when: Building ML solutions with SAP HANA's in-database machine learning using Python hana-ml library for PAL/APL algorithms, DataFrame operations, AutoML, model persistence, and visualization. Keywords: hana-ml, SAP HANA, machine learning, PAL, APL, predictive analytics, HANA DataFrame, ConnectionContext, classification, regression, clustering, time series, ARIMA, gradient boosting, AutoML, SHAP, model storage
Manifests2
{
"name": "sap-hana-ml",
"version": "2.4.1",
"description": "SAP HANA Machine Learning Python Client (hana-ml) development skill. Use when: Building ML solutions with SAP HANA's in-database machine learning using Python hana-ml library for PAL/APL algorithms, DataFrame operations, AutoML, model persistence, and visualization. Keywords: hana-ml, SAP HANA, machine learning, PAL, APL, predictive analytics, HANA DataFrame, ConnectionContext, classification, regression, clustering, time series, ARIMA, gradient boosting, AutoML, SHAP, model storage",
"author": {
"name": "Eduard Jiglau",
"email": "hello@sap-ai-skills.com",
"url": "https://sap-ai-skills.com"
},
"homepage": "https://sap-ai-skills.com",
"repository": "https://github.com/secondsky/sap-skills",
"license": "GPL-3.0",
"keywords": [
"cloud",
"database",
"hana",
"hdi",
"python",
"sap",
"sap-hana-ml",
"sql",
"sqlscript"
],
"skills": "./skills/",
"interface": {
"displayName": "SAP HANA Ml",
"shortDescription": "SAP HANA Machine Learning Python Client (hana-ml) development...",
"longDescription": "SAP HANA Machine Learning Python Client (hana-ml) development skill. Use when: Building ML solutions with SAP HANA's in-database machine learning using Python hana-ml library for PAL/APL algorithms, DataFrame operations, AutoML, model persistence, and visualization. Keywords: hana-ml, SAP HANA, machine learning, PAL, APL, predictive analytics, HANA DataFrame, ConnectionContext, classification, regression, clustering, time series, ARIMA, gradient boosting, AutoML, SHAP, model storage",
"developerName": "Eduard Jiglau",
"category": "HANA",
"capabilities": [
"Interactive",
"Read",
"Write"
],
"defaultPrompt": [
"Use SAP HANA Ml for SAP guidance."
],
"websiteURL": "https://sap-ai-skills.com"
}
}{
"name": "sap-hana-ml",
"description": "SAP HANA Machine Learning Python Client (hana-ml) development skill. Use when: Building ML solutions with SAP HANA's in-database machine learning using Python hana-ml library for PAL/APL algorithms, DataFrame operations, AutoML, model persistence, and visualization. Keywords: hana-ml, SAP HANA, machine learning, PAL, APL, predictive analytics, HANA DataFrame, ConnectionContext, classification, regression, clustering, time series, ARIMA, gradient boosting, AutoML, SHAP, model storage",
"version": "2.4.1",
"author": {
"name": "Eduard Jiglau",
"email": "hello@sap-ai-skills.com",
"url": "https://sap-ai-skills.com"
},
"license": "GPL-3.0",
"homepage": "https://sap-ai-skills.com",
"repository": "https://github.com/secondsky/sap-skills",
"keywords": [
"cloud",
"database",
"hana",
"hdi",
"python",
"sap",
"sap-hana-ml",
"sql",
"sqlscript"
],
"category": "hana",
"commands": [
"./commands/hana-ml-experiment-plan.md"
]
}