Machine Learning (ML) is a branch of Artificial Intelligence (AI) that empowers computer systems to learn from data and experiences, enhancing their performance over time without explicit programming for each task.
1. Definition and Core Concept:
Learning from Data:ML algorithms process and analyze large datasets to identify patterns and make informed decisions or predictions based on new, unseen data.
Improvement Over Time:Through iterative processes, ML models refine their accuracy and efficiency as they are exposed to more data, leading to continuous performance enhancement.
2. Types of Machine Learning:
Supervised Learning:Models are trained on labeled datasets, where the desired output is known, to make predictions or classifications.
Unsupervised Learning:Models work with unlabeled data to identify inherent structures or patterns without predefined outcomes.
Reinforcement Learning:Systems learn by interacting with an environment, receiving feedback in the form of rewards or penalties, and adjusting actions accordingly.
3. Applications in SAP's AI Solutions:
SAP AI Core and AI Launchpad:SAP provides a unified framework for managing and deploying ML models, facilitating seamless integration into business processes.
Generative AI Hub:This platform offers access to a variety of large language models (LLMs) and supports the orchestration of AI tasks, enabling the development of AI-driven applications.
