This article details a work we did in collaboration with the French administration (DINSIC) and a French supreme court (Cour de cassation) around 2 well-known Named Entity Recognition (NER below) libraries, Spacy and Zalando Flair. Spacy accuracy was too limited for our needs, and Flair was too slow. At the end we optimized Flair up […]
Natural language understanding (NLU) and language translation are key to a range of important applications, including identifying and removing harmful content at scale and connecting people across different languages worldwide. Although deep learning–based methods have accelerated progress in language processing in recent years, current systems are still limited when it comes to tasks for which […]
It would be easy to argue that Natural Language Toolkit (NLTK) is the most full-featured tool of the ones I surveyed. It implements pretty much any component of NLP you would need, like classification, tokenization, stemming, tagging, parsing, and semantic reasoning. And there’s often more than one implementation for each, so you can choose theexact […]
Machine learning systems often act on “features” extracted from input data. In a natural-language-understanding system, for instance, the features might include words’ parts of speech, as assessed by an automatic syntactic parser, or whether a sentence is in the active or passive voice. Some machine learning systems could be improved if, rather than learning from […]
In this article, we’ll have a look at how you can implement a content-based recommendation system using Python and the scikit-learn library. But before diving straight into this, it’s important to have some prerequisite knowledge of the different ways by which recommendation systems can recommend an item to users. Content-based: A content-based recommendation finds similar […]
Zalando research brings the latest flair to the scene. (Yes, that Zalando. The German-based fashion and beauty online shop operates in fifteen different European countries.) Flair is a simple framework for state-of-the-art natural language processing. It builds on top of Pytorch – a popular deep learning platform, which makes it easy to use. A powerful […]
Last Christmas, I went through the most frustrating experience as a consumer. I was doing some last minute holiday shopping and after standing in a long line, I finally reached the blessed register only to find out that my debit card was blocked. I could sense the old lady at the register judging me with […]
The Intel AI Lab has open-sourced a library for natural language processing to help researchers and developers give conversational agents like chatbots and virtual assistants the smarts necessary to function, such as name entity recognition, intent extraction, and semantic parsing to identify the action a person wants to take from their words. The first-ever conference […]
This post is a lay-person’s introduction to our new paper, which shows how to classify documents automatically with both higher accuracy and less data requirements than previous approaches. We’ll explain in simple terms: natural language processing; text classification; transfer learning; language modeling; and how our approach brings these ideas together. If you’re already familar with […]
spaCy is a popular and easy-to-use natural language processing library in Python. It provides current state-of-the-art accuracy and speed levels, and has an active open source community. However, since SpaCy is a relative new NLP library, and it’s not as widely adopted as NLTK. Source: towardsdatascience