The machine learning (ML) journey requires continuous experimentation and rapid prototyping to be successful. In order to create highly accurate models, data scientists have to first experiment with feature engineering, model selection, and optimization techniques. These processes are traditionally time-consuming and expensive. In this session, learn how low-code tools, including Amazon SageMaker Data Wrangler, Amazon SageMaker Autopilot, and Amazon SageMaker JumpStart, make it easier to experiment faster and bring highly accurate models to production more quickly and efficiently.

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