Machine Learning Model Deployment
The concept name provided is "undefined," so no specific SAP developer concept can be accurately defined. Based on the available sources, the closest supported topic relates to deploying and undeploying machine learning models on SAP Business Technology Platform: once training has successfully completed for a model, it can be deployed so that it is available for generating predictions. Developers can also manage the full lifecycle of such models using Intelligent Scenario Lifecycle Management, which provides tooling to oversee intelligent scenarios from training through deployment.
Tutorials that teach this
- Tutorial Use Data Attribute Recommendation to Train a Machine Learning Model
- Tutorial Use the Invoice Object Recommendation (IOR) Business Blueprint to Predict Financial Objects
- Tutorial Deploy Model and Get Prediction Results
- Tutorial Get an Understanding of CoreML
- Tutorial Get Recommendations Based on Users' Browsing History
- Tutorial Use the Sales Order Completion (SOC) Business Blueprint to Train a Machine Learning Model
- Tutorial Make Predictions for House Prices with SAP AI Core
- Tutorial Use the Regression Model Template to Train a Machine Learning Model
- Tutorial Deploy a Movie Recommendation System to AI Core Using Template Generator
- Tutorial Use Machine Learning to Extract Information from Documents with the SAP Document AI Basic UI
Docs explaining this concept
Discovery missions teaching this
Prerequisites
- Concept Predictive Modeling and Model Training The concept provided is **undefined** — no concept name was supplied for this entry. Please provide a valid SAP developer concept so that an accurate, source-grounded definition can be written.
- Concept SAP AI Core Service Setup The concept name was not provided, so a precise definition cannot be constructed from the available sources. Based on the sources, these materials collectively cover building and integrating [Generative AI applications](https://architecture.learning.sap.com/docs/golden-path/ai-golden-path/2-build-and-deliver/3-genai-applications/readme) on SAP Business Technology Platform using SAP AI Core — a managed service that developers use to train models, run AI workloads, and connect to large language models via orchestration. Developers leverage it alongside [SAP BTP service instances and keys](https://help.sap.com/docs/btp/sap-business-technology-platform/5b35ee98403045309bb0f8c7f0c79365?locale=en-US&state=PRODUCTION&version=Cloud) to authenticate and consume AI capabilities such as prompt optimization, grounding, multimodal responses, and custom evaluation within their applications.
- Concept ML Training Lifecycle Management The concept name was not provided (marked as "undefined"), and the supplied sources do not contain enough overlapping, clearly attributable content to construct a grounded 2–4 sentence definition for a specific, identifiable SAP developer concept. Please provide the concept name and ensure the source snippets contain sufficient detail to support a definition.
- Concept Docker Image Build and Publish The provided sources do not contain sufficient information to write a grounded definition for an **undefined** concept. The sources cover a range of SAP BTP topics (HANA connection issues, Kyma runtime, AI Core, Cloud Foundry) but do not define or describe a specific named concept that can be documented here.
Concepts that build on this
- Concept Embedding AI-Powered Functionality in Mobile Apps
- Concept SAP Personalized Recommendation Service
- Concept Pre-trained Model Integration
- Concept Service Ticket Intelligence
- Concept Named Entity Recognition (NER) with Pre-trained Models
- Concept Core ML Model Integration in Xcode
- Concept Inference Request
- Concept Document Information Extraction
- Concept Machine Learning Inference
- Concept Machine Learning Model Training
- Concept Machine Learning Model Undeployment