Does it support automated machine learning?

Yes, it includes full support for the Automated Predictive Library (APL) for automated classification, regression, and feature engineering with minimal manual configuration.

Can I visualize model results with this skill?

Absolutely. The skill provides access to 14 specialized visualization modules for EDA, model metrics, and SHAP-based model interpretability.

How does the DataFrame handling work in this skill?

It uses lazy evaluation, meaning operations build optimized SQL queries that are only executed in the database when you explicitly call for the results (e.g., using .collect()).

What is the primary benefit of using this skill?

It enables in-database machine learning, allowing you to process massive datasets without moving data out of SAP HANA, ensuring high performance, reduced latency, and enhanced data security.

Which SAP HANA versions are compatible?

This skill supports SAP HANA 2.0 SPS03 or higher, as well as SAP HANA Cloud environments, using the Python 3.8+ runtime.

SAP HANA Machine Learning (hana-ml)

Name: SAP HANA Machine Learning (hana-ml)
Author: dherbe-digital

bydherbe-digital

0•

データサイエンスとML

Develops and deploys in-database machine learning models using the SAP HANA Python Client (hana-ml).

The sap-hana-ml skill empowers developers to build, train, and manage machine learning models directly within SAP HANA using the Python hana-ml library. It provides comprehensive support for the Predictive Analysis Library (PAL) and Automated Predictive Library (APL), enabling high-performance in-database processing through lazy-evaluation DataFrames. This skill is ideal for data scientists and developers working with SAP data who need to implement complex algorithms like Gradient Boosting, ARIMA, or AutoML while maintaining data security and minimizing data movement by keeping processing within the database layer.

主な機能

01Built-in visualization modules for Exploratory Data Analysis (EDA) and model performance metrics

02Comprehensive model management including persistence, storage, and SHAP-based interpretability

03Efficient in-database processing using lazy-evaluation DataFrames to minimize data transfer

04Full integration with SAP HANA's Predictive Analysis Library (PAL) and Automated Predictive Library (APL)

05Automated Machine Learning (AutoML) capabilities for automated classification and regression

060 GitHub stars

ユースケース

01Automating time-series forecasting for supply chain optimization using ARIMA and PAL algorithms

02Developing interpretable classification models for financial fraud detection with SHAP visualizations

03Building predictive maintenance models directly on enterprise ERP data within SAP HANA

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add dherbe-digital/nova-skills-collection sap-hana-ml

For use in Claude.ai and ChatGPT

Download Skill