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How Azure Anomaly Detection API allows you to find weirdness inside crowd – Part 2 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…

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: Natural Language Processing (Azure NLP) is a field in computer science concerned with computational techniques to analyze and synthesize natural language and speech. In simple words, it is the science behind daily assistants who understand our words such as iPhone Siri and Google Assistant. The Azure NLP field is among the most challenging areas in computer science. The reason is that computers are very good at performing mathematical operations and their aggregates, however, NLP…

Now, we continue what we started in (Sentiment Analysis-Guide to Call Center Performance – 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 of NLP (Natural Language Processing). It consists of the 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 to 1 or…

Sentiment Analysis Tools: Guide to Call Center Performance -1 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…

A little background … Big data analytics and AI has seen applications in many fields such as finance, trade, and health sectors. Recently, HR and talent domains started enjoying the benefits of these technologies, where it is called “people analytics.” This article begins by questioning the status quo of the current talent management practices and highlight its flaws, thereafter it paves the path for the rise of people analytics. Then, people analytics contemporary position is…

NOTE: Find an updated version here Background … Few of years ago, writing a software application that performs any sort of ”intelligence” was not the easiest task to do. Considerable know-how around certain frameworks and libraries need to be established, which means learning curve, dollars money, and a risk that many were unwilling to take. I remember 8 years ago, when I was planning to implement some object tracking algorithm for a university project, I…