Understanding the Basics of Text Classification
Explore the basics of text classification using spaCy, understanding how to assign predefined labels to text data. This lesson covers key types like binary, multiclass, and multilabel classification, common use cases such as sentiment analysis and spam detection, and the importance of labeled datasets for training models.
We'll cover the following...
Text classification is the task of assigning a set of predefined labels to text. Given a set of predefined classes and some text, you want to understand which predefined class this text falls into. We have to determine the classes ourselves by the nature of our data before starting the classification task. For example, a customer review can be positive, negative, or neutral.
Text classifiers are used for detecting spam emails in your mailbox, determining the sentiment of customer's reviews, understanding customer's intent, sorting customer's complaint tickets, and so on.
Text classification is a fundamental task of NLP. It is gaining importance in the business world as it enables businesses to automate their processes. One ...