Re-posted from the Microsoft Azure blog.
Artificial Intelligence (AI) is a hugely disruptive force, one that is powering much of the digital transformation businesses are going through in recent times. At Microsoft, our mission is to bring AI to every developer and every organization on the planet, and to help businesses augment human ingenuity in unique and differentiated ways.
Developers and data scientists are at the heart of this transformation and the mission for the Microsoft AI platform is to offer the very best tools to make them successful in this journey. These include tools for automating machine learning through the pre-built AI capabilities we offer for vision, speech, language, knowledge and search in the form of the Microsoft Cognitive Services, which are enabling a rich variety of customer scenarios. As an example, when we announced the general availability of our conversational AI tools last month, we showcased innovative applications from leading edge customers such as Molson Coors, UPS and many others.
We continue to innovate on our AI platform at a rapid pace and wish to make AI easy by bringing capabilities such as transfer learning and automated machine learning to developers.
In this context, we are excited about the Microsoft Custom Vision Service, which makes it possible for you to easily train a classifier with your own data, export the models and embed these custom classifiers directly in your applications, and run it offline in real time on iOS, Android and many other edge devices. The Custom Vision Service is a cloud enabled tool for easily training, deploying and improving custom image classifiers. With just a handful of images per category, developers can train their own image classifier in minutes through a simple drag and drop interface.
Once you have created and trained your custom vision model through the service, its trivial to get your model exported from the service, allowing developers to take their custom model with them to any environment (i.e. regardless of whether their scenario requires that the model run on-premises, in the cloud, or on mobile or edge devices). This provides a flexible, easy way for developers to export and embed custom vision models in minutes, and with no coding.
Custom Vision Service is designed to build quality classifiers with very small training datasets, helping you build a classifier that is robust to differences in the items you are trying to recognize, and which ignores the things you are not interested in.
ML Blog Team