NLP Landscape: Switzerland

Natural Language Processing has seen some major breakthroughs in the past years; with the rise of Artificial Intelligence, the attempt at teaching machines to master human language is becoming an increasingly popular field in academia and industry all over the world. Switzerland is no exception: with its unique linguistique diversity, its central location within Europe

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The three levels of NLP for your business

In the past years, the tech world has seen a surge of NLP applications in various areas including adtech, publishing, customer service and market intelligence. According to Gartner’s hype cycle, NLP has reached the peak of inflated expectations in 2018, and many businesses see it as a “go-to” solution to generate value from the 80%

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Emoticon Use From East to West

Emoticons become ever more prevalent in the text-based communications of today, giving context for written communication such as emails, texts and online forum posts. Just as facial expressions and body language do in personal interactions, these animations serve a similar purpose. If a business or brand intends to succeed in their messaging across cultural and

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Popular Machine Learning Data Skills

Machine learning is a rapidly growing segment of computer science and engineering. The discipline combines skills from multiple areas including programming, computer science, information technology, data science and engineering. The general idea behind machine learning is to give computers the ability to learn without being explicitly programmed. They are valuable for any business and customer

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Write for us (and get paid)!

Dear readers, If you have some great content that you would like to share with your peers, we have some great news for you. From now onwards, we will be accepting high quality guest blog posts for publishing in the NLPPeople blog on a paid basis. There are only two requirements to the content we

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New Open Source Tool – TM Cleaner

We are happy to announce Translation Memory (TM) Cleaner , a software for identifying the translation units in translation memories or parallel corpora that contains segments that are not translations of each other. TM Cleaner has the following features : 1. It is written in python and java. 2. It is hosted at github :

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