Interview Guides
You are building a text classification model for a product that routes incoming messages into a small set of labels. The text is noisy, short, and often includes slang, misspellings, emojis, and product-specific terms. You need to decide which text features to create, how to preprocess the text, and how to balance sparse features with embedding-based features.
How do you approach feature engineering for a natural language processing task?
