Look at the technologies around us:
- Spellcheck and autocorrect
- Auto-generated video captions
- Virtual assistants like Amazon’s Alexa
- Your news site’s suggested articles
What do they have in common?
All of these handy technologies exist because of natural language processing! Also known as NLP, the field is at the intersection of linguistics, artificial intelligence, and computer science. The goal? Enabling computers to interpret, analyze, and approximate the generation of human languages (like English or Spanish).
NLP got its start around 1950 with Alan Turing’s test for artificial intelligence evaluating whether a computer can use language to fool humans into believing it’s human.
But approximating human speech is only one of a wide range of applications for NLP! Applications from detecting spam emails or bias in tweets to improving accessibility for people with disabilities all rely heavily on natural language processing techniques.
NLP can be conducted in several programming languages. However, Python has some of the most extensive open-source NLP libraries, including the Natural Language Toolkit or NLTK. Because of this, you’ll be using Python to get your first taste of NLP.
Don’t worry if you don’t understand much of the content right now — you don’t need to at this point! This lesson is an introductory overview of some of the main topics in NLP and you’ll get to dive deeper into each topic on its own later.