AI, in the context of cloud computing, is based around a broad range of services, the core of which is machine learning. Machine learning is a data science technique that allows computers to use existing data to forecast future behaviors, outcomes, and trends. Using machine learning, computers learn without being explicitly programmed.
Forecasts or predictions from machine learning can make apps and devices smarter. For example, when you shop online, machine learning helps recommend other products you might like based on what you’ve purchased. Or when your credit card is swiped, machine learning compares the transaction to a database of transactions and helps detect fraud. And when your robot vacuum cleaner vacuums a room, machine learning helps it decide whether the job is done.
Here are some of the most common AI and machine learning service types in Azure.
|Azure Machine Learning Service||Cloud-based environment you can use to develop, train, test, deploy, manage, and track machine learning models. It can auto-generate a model and auto-tune it for you. It will let you start training on your local machine, and then scale out to the cloud.|
|Azure ML Studio||Collaborative visual workspace where you can build, test, and deploy machine learning solutions by using prebuilt machine learning algorithms and data-handling modules.|
A closely related set of products are the cognitive services. You can use these prebuilt APIs in your applications to solve complex problems.
|Vision||Use image-processing algorithms to smartly identify, caption, index, and moderate your pictures and videos.|
|Speech||Convert spoken audio into text, use voice for verification, or add speaker recognition to your app.|
|Knowledge mapping||Map complex information and data to solve tasks such as intelligent recommendations and semantic search.|
|Bing Search||Add Bing Search APIs to your apps and harness the ability to comb billions of webpages, images, videos, and news with a single API call.|
|Natural Language processing||Allow your apps to process natural language with prebuilt scripts, evaluate sentiment, and learn how to recognize what users want.|