Category

Cognitive Services

Category

Introduction: As I have discussed many times before, the AI services landscape is aggressively growing and developing. Microsoft, AWS, IBM, and Google are in a crazy race to roll-out the most attractive services to the market, it is going fast to the extent that I usually question my last month knowledge if I get asked for the recommendation! Last weeks, Microsoft had rolled out new services in their platform, which are: Immersive Reader, Personalizer, Form…

Last Wednesday, I had the pleasure to present Cloud AI at Stockholm Azure Meetup where I discussed the concept of Cloud AI, state of art and the business possibilities that can be achieved by utilizing it. The presentation started by comparing the classical machine learning with”Cloud AI or AI as a Service” approach and discussed the pros and cons of each. The audience were engaged and there have been many questions and inquiries, I am…

Introduction In the previous blog post, we introduced the newly launched anomaly detector service, discussed its use cases, weaknesses and strengths. Today, we will take our discussion deeper and inspect the API request/response model, parameters meaning and how can we have some control over the API. Using the API Similar to other cognitive services, anomaly detector relies on a RESTful API to provide its service. Since using RESTful APIs is straight forward for any regular…

Introduction Firstly, I would like to apologize that last April I blogged only two blog posts since it was a pretty hectic month for my beloved country where our people have overthrown a 30 years dictator. I was spending most of my time following news and expert’s analysis. Last month, we were talking about some things that will MAKE YOUR CAREER SMARTER (Software is Eating the World Part 1 & Part 2). Today we will…

Introduction: In the previous articles (e.g., Smart OCR), we discussed how a developer could inject an AI service to his/her application to make it perform a smart task such as image recognition and voice recognition. Moreover, we discussed the benefits that are entailed from using AI services such as lower TCO (total cost of ownership) and easier updates. Kindly note that I use AI services and cognitive services interchangeably in this article, so don’t get…

Now, we continue what we started in (The Unconventional Guide to Call Center Performance Analysis using AI – Part 1), and implement a really cool step, which is sentiment analysis. Sentiment analysis Sentiment analysis is among the most exciting problems in the field on NLP (Natural Language Processing). It consists of identification of a text attitude towards a topic, positively or negatively, and returning a score between some maximum negative and maximum positive (e.g., 0…

Background Objective measurement of unstructured data such as video, text, and audio has always been a challenge for BI, which is primarily focused on structured data, big data analytics aims to bridge this gap by its ability to analyze unstructured data. This is closely related to what we are going to do in today’s tutorial using AI services. Daily, we deal with different organizations, companies and service firms that provide call centers endpoint such telephone…

Hello friends, This tutorial we will start getting our hands dirty – That is, we will begin developing a real AI software that solves a genuine business problem so that you feel both learning and developing something that has a value proposition. Let me start with a frequent problem I face; As a Muslim, I have dietary constraints with regards to food components and E numbers. I spend considerable time in the supermarket attempting to…

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