The article narrates a personal anecdote by Burmistrov, illustrating the challenges of debugging machine learning models through a relatable family story. After an arduous debugging process, Burmistrov excitedly shares the success of his team’s model to little reaction from his wife. This leads to a comparison of debugging challenges in both models and relationships. He emphasizes the importance of providing quality data to models and introduces the concept of feature platforms, which facilitate the delivery of good data for machine learning models.
When you're mad at me, you don't simply tell me what's wrong. I have to spend so much time figuring out what's going on, just like you guys with this model.
The models are really hard to debug. If you build a model and it's underperforming, it can be a nightmare in debugging.
The least we can do to ease the pain is to ensure that the data that we feed to the model is ok, so the data doesn't contain these bugs.
Feature platforms aim to deliver good data for machine learning models.
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