However you look at it, we’re coexisting with machines now. Although we’re still a long way from The Matrix (hopefully?), we’ve already stepped into areas that were only science fiction a decade ago.
Compared to us, computer programs, algorithms, and apps work on a whole different level due to their substantial complexity that’s only increasing with time. Yet we are happy to completely surround ourselves with them because they make our lives incomprehensibly easier. How is that even possible?
This is thanks to natural language processing (NLP)—the ability of computer programs to understand human language as it’s spoken and written. Even though we may never understand what an AI is thinking, with NLP we can now build a machine that uses language just like we humans do.
As the most widespread programming language in the world, Python is no stranger to natural language processing. In fact, there is a wide variety of excellent Python libraries that NLP engineers can take advantage of.
Read our article to discover what natural language processing is all about, what are its main challenges, and which top NLP libraries are actually worth your time!