What is machine learning?
Machine learning (ML) is the process of using mathematical models of data to help a computer learn without direct instruction. It’s considered a subset of artificial intelligence (AI). Machine learning uses algorithms to identify patterns within data, and those patterns are then used to create a data model that can make predictions. With increased data and experience, the results of machine learning are more accurate—much like how humans improve with more practice.
The adaptability of machine learning makes it a great choice in scenarios where the data is always changing, the nature of the request or task are always shifting, or coding a solution would be effectively impossible.
Machine learning techniques
There are three main techniques that people use in machine learning:
Addressing datasets with labels or structure, data acts as a teacher and “trains” the machine, increasing in its ability to make a prediction or decision.
Addressing datasets without any labels or structure, finding patterns and relationships by grouping data into clusters.
Replacing the human operator, an agent—a computer program acting on behalf of someone or something—helps determine outcome based upon a feedback loop.
Azure Machine Learning
Empower data scientists and developers to build, deploy, and manage high-quality models faster and with confidence. Accelerate time to value with industry-leading MLOps (machine learning operations), open-source interoperability, and integrated tools. Innovate on a secure, trusted platform designed for responsible machine learning (ML).
- Rapidly build and train models
- Operationalize at scale
- Deliver responsible solutions
- Innovate on a more secure hybrid platform
|Automated machine learning
|Drag-and-drop machine learning
|Responsible machine learning
|Model registry and audit trail
|Git and GitHub
|Deep integration with other Azure services
|Hybrid and multicloud support