Bringing Google AutoML to 3.5 million data scientists on Kaggle

Recently, Kaggle hit a significant milestone by surpassing over 3.5 million users that use our platform to learn and apply machine learning. AI is one of the world’s most powerful emerging technologies, but even with its growing numbers, its adoption has been hampered by the limited amount of data scientists who have access to the tools and expertise to leverage it effectively. Kaggle’s mission is to empower our community of data scientists by providing them with the skills and tools they need to lead in their field, and now we’re advancing that mission by integrating AutoML into our platform.

Why we’re excited about AutoML

AutoML stepped into our spotlight earlier this year, where it led for most of our all-day machine learning competition at Kaggle Days at Cloud Next ’19, before being narrowly edged out by a team of data scientists in the closing moments of the event. The strong performance even made headlines and generated excitement for its future.

What especially drew our interest was that the team using AutoML was able to get strong performing results quickly, with low effort and no domain expertise or supervision. What’s more, they spent very little time on data prep, and virtually no time on feature engineering, model selection, and hyperparameter tuning. The time efficiency of AutoML became even more clear during the IEEE competition, where it took thousands of teams several weeks to beat the AutoML benchmark by a significant margin on our private leaderboard.