Text classification is one of the most practical skills in Natural Language Processing. Whenever we automatically categorise emails into spam and non spam, label product reviews as positive or negative, or route support tickets to the right department, we are…
Natural language is deeply tied to time and to real usage in communities. When people describe events, they specify when something happened, how long it lasted and how different events relate in time. At the same time, they learn and…
Sentiment analysis is one of the most popular and widely deployed applications of Natural Language Processing. Whenever a company wants to measure customer satisfaction from reviews, a political analyst wants to monitor public opinion on social media or a product…
So far in this course, most of the focus has been on processing words and sentences at the level of forms. We have learned how to clean text, build language models and assign part of speech tags. The next step…
Language is not just a bag of words. The way words are ordered and grouped gives sentences their structure and meaning. Natural Language Processing systems must therefore understand more than isolated tokens. they need at least a partial grasp of…
Many Natural Language Processing tasks can be described as sequence labelling. There is an input sequence of words and for every word we want to predict a label. Part of speech tagging is one of the most important examples. For…