Interview Guides
You are building a text classification model for a stream of short customer messages. The raw text includes typos, emojis, URLs, product names, and repeated boilerplate, so the first step is deciding which features actually help the model separate classes. You need to explain how you would extract and combine useful features before training.
How do you approach the problem of feature extraction in natural language processing?
