Microsoft Azure
Machine Learning
How machine learning works
A team of botanists and scientists collect data on wildflower samples.
The team labels the samples with the correct species.
The labeled data is processed using an algorithm that finds relationships between the features of the samples and the labeled species.
The results of the algorithm are encapsulated in a model.
When new samples are found by volunteers, the model can identify the correct species label.
Machine learning in Microsoft Azure
Microsoft Azure provides the Azure Machine Learning service - a cloud-based platform for creating, managing, and publishing machine learning models.
| Feature | Capability |
|---|---|
Automated machine learning | This feature enables non-experts to quickly create an effective machine learning model from data. |
Azure Machine Learning designer | A graphical interface enabling no-code development of machine learning solutions. |
Data and compute management | Cloud-based data storage and compute resources that professional data scientists can use to run data experiment code at scale. |
Pipelines | Data scientists, software engineers, and IT operations professionals can define pipelines to orchestrate model training, deployment, and management tasks. |
Anomaly Detection
a machine learning based technique that analyzes data over time and identifies unusual changes.
Example
Sensors in the car collect telemetry, such as engine revolutions, brake temperature, and so on.
An anomaly detection model is trained to understand expected fluctuations in the telemetry measurements over time.
If a measurement occurs outside of the normal expected range, the model reports an anomaly that can be used to alert the race engineer to call the driver in for a pit stop to fix the issue before it forces retirement from the race.
Computer Vision
| Service | Capabilities |
|---|---|
Computer Vision | You can use this service to analyze images and video, and extract descriptions, tags, objects, and text. |
Custom Vision | Use this service to train custom image classification and object detection models using your own images. |
Face | The Face service enables you to build face detection and facial recognition solutions. |
Form Recognizer | Use this service to extract information from scanned forms and invoices. |
Natural Language Processing
| Service | Capabilities |
|---|---|
Text Analytics | Use this service to analyze text documents and extract key phrases, detect entities (such as places, dates, and people), and evaluate sentiment (how positive or negative a document is). |
Translator Text | Use this service to translate text between more than 60 languages. |
Speech | Use this service to recognize and synthesize speech, and to translate spoken languages. |
Language Understanding Intelligent Service (LUIS) | Use this service to train a language model that can understand spoken or text-based commands. |
Conversational AI
| Service | Capabilities |
|---|---|
QnA Maker | This cognitive service enables you to quickly build a knowledge base of questions and answers that can form the basis of a dialog between a human and an AI agent. |
Azure Bot Service | This service provides a platform for creating, publishing, and managing bots. Developers can use the Bot Framework to create a bot and manage it with Azure Bot Service - integrating back-end services like QnA Maker and LUIS, and connecting to channels for web chat, email, Microsoft Teams, and others. |
Azure Machine Learning Workspace
Automated ML
Designer
Demos
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