Future Ready Talent https://futurereadytalent.in/ is a virtual internship platform with an opportunity to learn the in-demand Azure cloud & security skills aligned to industry needs. The program aims at preparing learners to work towards solving business challenges and creating innovative solutions using the power of Microsoft Azure & GitHub tools.
I used Cognitive Services in one of my project which brings AI within reach of every developer and data scientist. With leading models, a variety of use cases can be unlocked. All it takes is an API call to embed the ability to see, hear, speak, search, understand and accelerate advanced decision-making into your apps. Enable developers and data scientists of all skill levels to easily add AI capabilities to their apps.
The space of cognitive services has grown up too fast with the advent of various pre-trained services provided by various public cloud providers such as Azure, AWS, or Google Cloud. This space has become more promising with its coverage to solve most of the common business use cases across industry domains. The post will mainly look into various Cognitive Services offered by Microsoft Azure, it is worthy to discuss the capabilities of each service and solutions which they can offer. This is going to be series of posts starting with an introduction to these services: 1) Cognitive Vision, 2) Cognitive Text Analytics, 3) Cognitive Language Processing, 4) Knowledge Processing and Search.
Embed facial recognition into your apps for a seamless and highly secured user experience. No machine-learning expertise is required. Features include face detection that perceives facial features and attributes—such as a face mask, glasses, or face location—in an image, and identification of a person by a match to your private repository or via photo ID.
Object detection is similar to tagging, but the API returns the bounding box coordinates for each tag applied. For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their coordinates in the image. You can use this functionality to process further relationships between the objects in an image. It also lets you know when there are multiple instances of the same tag in an image. Generate a description of an entire image in human-readable language, using complete sentences. Computer Vision's algorithms generate various descriptions based on the objects identified in the image. The descriptions are each evaluated and a confidence score generated. A list is then returned ordered from highest confidence score to lowest.