Implement a smoothed n-gram language model and compute perplexity on held-out text.
Ahead of transformers, this was the language model, and it remains the clearest way to prove you grasp what perplexity truly measures. Smoothing is where people slip up. Here is the implementation.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Ahead of transformers, this was the language model, and it remains the clearest way to prove you grasp what perplexity truly measures. Smoothing is where people slip up. Here is the implementation.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
