One of the flaws of usual training data generation is that, when you ask somebody to manually create training data for you, they will make an effort to write these sentences correctly, following the spelling and punctuation norms of your language. Even if some errors appear, they will be minimal, because they are trying to do things right —this is, to provide “orthographically right” sentences.

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Two concepts, one mission: to make machines understand humans. Natural Language Processing (NLP) and Machine Learning (ML) are all the rage right now as techniques that complement each other rather than as NLP vs ML. In this post,  we will focus on NLP and how it works together with ML to solve the challenges Artificial Intelligence is posing.

Sentiment Analysis is a procedure used to determine if a chunk of text is positive, negative or neutral. In text analytics, natural language processing (NLP) and machine learning (ML) techniques are combined to assign sentiment scores to the topics, categories or entities within a phrase.

While a picture may be worth a thousand words – a thousand words may be worth thousands of dollars. Never thought how valuable all your company unstructured data would be? This heterogeneous knowledge can turn out to be quite useful for companies, however, there is still much to be learned. 

Has your name or surname ever been mocked? In many languages, people are really embarrassed to have unusual names that make other people laugh. Some names and surnames are treated even as insulting or offensive in some cases.