All posts by Cennest

GraphQL server with .NET Framework ( not .NET CORE)

In a recent post we had listed out analysis done and conclusions made when asked by a customer to convert their existing API to GraphQL. While exploring GraphQL with .NET framework we realized there is a large gap in examples and demos on using GraphQL with full scale .NET framework and EntityFramework. We took some […]

Extracting Text from Images:- Google a notch better than Azure and AWS!

Extracting text from images has been worked on for many years now and finds applications in many domains like Banking , Legal, Healthcare, education and entertainment! With the advent of machine learning, text extraction from images is being offered as a Cognitive API by many AI/ML providers like AWS Rekognition, Azure Computer Vision,and Google CloudVision […]

Cognitive Image Analysis:- Azure and Google come out winners!

Image Analysis is defined in wikipedia as “…the extraction of meaningful information from images; mainly from digital images by means of digital image processing techniques” With the advent of machine learning, Image Analysis is being offered as a Cognitive API offering by many AI/ML providers like AWS Recognition , Azure Computer Vision,and Google CloudVision  . […]

Introducing the Cognitive API Integrator

We are launching the Cognitive API Integrator today for developers, Engineering Managers, CIOs or anyone who needs to choose a Cognitive Service provider to build out a business service. Our Cognitive API Integrator aggregates cognitive services across major providers (currently Microsoft Azure, Amazon Web Services & Google Cloud) and provides all the results against a […]

ML Series – #0:- AI, ML, Auto-ML, Cognitive Services and all that Jazz!!!

We live in a world of buzzwords!! Media, news, professional and self opinioned blogs, articles and magazines don’t really help when it comes to untangling the mesh of words that come with any new technological advancement! The latest buzzwords in the happening “IT” world today are AI, ML, Deep Learning, Cognitive Services, Auto-ML and the […]

ML Series–#6:- Is Random Sampling good enough?

Picking up on the last article where we talked about the first few steps we take when exploring our data, the last step i.e Data cleaning is probably the most time and resource intensive step. One of the first things you do when presented with a data sample (probably even before the Explore and Correlate […]