Personalized automated machine learning

This invention describes a computer system that learns to recommend the best machine learning models to individual users. It works by training a neural network with data about a user's profile, then using that network to figure out which models are most relevant to them, displaying a personalized list with a relevance score for each. The claims specifically focus on using user profile data to train the initial network.

Why it matters: Filed when AutoML was still maturing. The intervening years have seen significant advancements in AutoML frameworks and the accessibility of powerful neural network architectures, making the implementation of such a personalization system more efficient and robust today.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedSoftware logic, machine learning expertise

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