Read on to learn more 8 amazing Python Natural Language Processing libraries that have over the years helped us deliver quality projects to our clients. There are many tools and libraries created to solve NLP problems. Now, developers can use ready-made tools that simplify text preprocessing so that they can concentrate on building machine learning models. In the past, only experts could be part of natural language processing projects that required superior knowledge of mathematics, machine learning, and linguistics. Since NLP relies on advanced computational skills, developers need the best available tools that help to make the most of NLP approaches and algorithms for creating services that can handle natural languages. There’s a reason why tech giants like Google, Amazon, or Facebook are pouring millions of dollars into this line of research to power their chatbots, virtual assistants, recommendation engines, and other solutions powered by machine learning. This is also why machine learning is often part of NLP projects.īut why are so many organizations interested in NLP these days? Primarily because these technologies can provide them with a broad range valuable insights and solutions that address language-related problems consumers might experience when interacting with a product.
Natural language processing (NLP) is a field located at the intersection of data science and Artificial Intelligence (AI) that – when boiled down to the basics – is all about teaching machines how to understand human languages and extract meaning from text.
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