hana-ml-samples and hana-ml-py-codejam
These are complementary learning resources where the CodeJam provides structured hands-on exercises and training content for the same SAP HANA ML stack that the samples project documents through code examples.
About hana-ml-samples
SAP-samples/hana-ml-samples
This project provides code examples for SAP HANA Predictive and Machine Learning scenarios and is educational content. It covers simple Predictive Analysis Library SQL examples as well as complete SAP HANA design-time “ML scenario”-application content or HANA-ML Python Notebook examples.
This project helps data professionals, developers, and analysts working with SAP HANA to understand and implement predictive and machine learning capabilities. It provides ready-to-use code examples for various ML scenarios, allowing you to learn how to apply algorithms directly within your SAP HANA database. You'll gain practical insights into using SAP HANA's built-in predictive libraries for tasks like forecasting, classification, and more.
About hana-ml-py-codejam
SAP-samples/hana-ml-py-codejam
Material (learning content and exercises) for SAP CodeJams on getting started with Machine Learning using SAP HANA Cloud and Python.
This material helps data professionals and developers learn how to apply machine learning within SAP HANA Cloud using Python. You'll work with your data in SAP HANA, apply various ML techniques like classification and preprocessing, and produce trained models and insights directly within the SAP ecosystem. This is for anyone looking to build intelligent applications leveraging SAP HANA Cloud's capabilities.
Scores updated daily from GitHub, PyPI, and npm data. How scores work