Build ML models w/ advanced configurations, gain Model Leaderboard visibility on SageMaker Canvas

Amazon SageMaker Canvas is a no-code workspace that enables analysts and citizen data scientists to generate accurate ML predictions for their business needs. Starting today, Canvas supports advanced model build configurations such as selecting training method (Ensemble/Hyper parameter optimization) and algorithms, customizing training/validation data split ratio, and setting limits on autoML iterations and job run time, thus allowing users to customize model building configurations without having to write a single line of code. This flexibility can provide more robust and insightful model development. Non-technical stakeholders can use the no-code features with default settings, while citizen data scientists can experiment with various ML algorithms and techniques, helping them understand which methods work best for their data and optimize to ensure the model’s quality and performance.

Source:: Amazon AWS