AI & Machine Learning using Cloud Vision

Google Cloud Vision offers both pre-trained models via an API and the ability to build custom models using AutoML Vision to provide flexibility depending on your use case.

Cloud Vision API enables developers to understand the content of an image by encapsulating powerful machine learning models in an easy-to-use REST API.

It quickly classifies images into thousands of categories (such as, “sailboat”), detects individual objects and faces within images, and reads printed words contained within images.

You can build metadata on your image catalog, moderate offensive content, or enable new marketing scenarios through image sentiment analysis.

Microsoft Azure, Google, Amazon, IBM, SAP and few other niche Players are all vying and competing in providing their cloud platforms, for not only allowing server-less programming platform of ML use cases, their set of API’s but also providing computing platform to create and new ML or deep learning models

They all offer almost same capabilities, There are subtle differences in what’s available to what degree in individual services for their pre-trained models.

Here is a for Play Application for Facial Recognition using Microsoft Azure Cognitive Services

It is possible to use Facial recognition to sentiment analysis of the subject or person , be it employee or customer by their picture, but also it can be used to verify the identity and used as steps in identity verification process.

Shared below are some of the test results using Google ML Libraries API’s.

If you are a sports fan of Chicago Teams, What did AI model think of following image



Table 1: AI Detected Meta Data of Team Logo
description score
Chicago Bulls 0.5919871

Did AI model correctly identified this famous monument in Paris ? verify by zooming its geo location identified by AI model

Table 3: AI Detected Meta Data of notre dame cathedral
description score
Notre Dame de Paris 0.9293472
Paris 0.8343095