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Data journalism (aka data-driven) is an emerging approach that involves techniques from several disciplines, including journalism, statistics, data science and data visualisation to tell a story about a specific topic.

Berret and Phillips define data journalism as: A field that encompasses a suite of practices for collecting, analyzing, visualizing, and publishing data for journalistic purposes.

61% of journalists analyze and use data to create stories at least weekly, a marked increase from 36% in 2017. This means that data journalism is far more common today.

In this article we will show you how to prepare a data-driven story and why…


In this article, I will use shortlyai to write about machine learning in finance. The purpose is to demonstrate the current SOTA models for language generation. The article is about applications of machine learning in finance.

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Applications of Machine Learning in finance

The applications of machine learning in finance are growing. There is much analysis to be done and the machine learning technique is proving its worth, with Bloomberg recently announcing an investment of $22 million in a new AI-based financial service. Let’s explore some of the current applications of Machine Learning (ML) and Artificial Intelligence (AI) in finance.

The use of machine learning and artificial…


Thoughts and Theory

Our presented dataset enables researchers to build and evaluate CLIR systems in English and Seven European languages in the medical domain.

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Introduction

In this story, I will present our contributions to extend existing Cross-Lingual Information Retrieval (CLIR) datasets that were released during the Information Retrieval (IR) tasks of CLEF eHealth Evaluation Lab. The resulted dataset aims at building and evaluating (CLIR) in the medical domain. The supported languages are English, Czech, French, German, Hungarian, Polish, Spanish, and Swedish.

What is Cross-Lingual Information Retrieval (CLIR)?

CLIR enables users to search for information by posing queries in a language that is different from the collection language. This helps to break the language barrier between system users and a vast amount of data that is represented in different language. …


As a Syrian, I can say that this is one of the best stories I've read recently, which attempts to spot what is going there and why.


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Text processing is a crucial task in Natural Language Processing; once you start working on some task, you quickly need to perform quick tasks such as counting, applying some regex for search or cleaning, fixing the character encodings, etc.

You probably know how to do all of this stuff in your favourite programming language, but trust me, once you know how to do it in bash, you will never use anything but bash to count unique words or do some cleaning. Bash is very quick, and you do not need to worry about pre-installed libraries or compatibility issues. …


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In this article, we showed how we employed millions of web pages to better understand personas, and let data decide what defines each one, and what keywords we should use when we want to include/exclude this persona from our ads campaign. I hope you found it useful and interesting, do not hesitate to tell us your opinion in the comments.

How can Personas be used in digital marketing?

A useful personas labeling can be used mainly in two contexts, as follows:

Marketing Campaigns

The e-Marketing campaigns are one of the essential tools for business owners to tell customers about their stories, added-values and the products they provide. However, there are…

Shadi Saleh, PhD

Senior Data Scientist at Datasentics, PhD holder in Cross-lingual Information retrieval in the Medical domain from UFAL-Charles University. I blog to chill.

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