Natural language processing is the part of AI that lets computers read, understand and generate human language. It sits behind search engines, spam filters, voice assistants, translation tools and chatbots, and it is the foundation that modern language models were built on.
The lessons start with a clear definition of what NLP is and the everyday applications it powers. Next you will see how computers can learn meaning from the way words are used, and trace how the field moved from hand-written rules to statistical methods and then to neural networks.
A longer university lecture introduces human language and word vectors, and the module ends with a short explainer on large language models, the technology that grew out of everything above. Watch the lessons in order, then continue on to Text Preprocessing.
A clear definition of NLP from IBM Technology, with examples of the NLP applications you meet every time you use the internet.
Video 9minShows how computers can learn meaning from how words are used (distributional semantics) and how a recurrent neural network can build sentences.
Video 13minTraces NLP from its rule-based beginnings in the 1950s, through statistical methods and embeddings, to neural networks and the Transformer.
Video 7minA short animated explainer from 3Blue1Brown on how large language models predict the next word, the technology that grew out of NLP.
Video 7min