Automatic Labelling and Model Tuning with Amazon SageMaker - AWS Summit Sydney
Developing machine learning models requires a lot of effort which often needs to be repeated over time as data distributions change. In this session you will learn about some of the latest concepts in Automatic Machine Learning including how to apply them to speed up development and achieve robust models over time. You will learn how to run a custom labelling job using Amazon SageMaker Ground Truth to build a larger data set to fine-tune your model. You will also learn how to tune your model’s hyperparameters using Amazon SageMaker’s Automatic Model Tuning capabilities and understand the theory of how bayesian optimisation is automatically applied for more accurate results and faster tuning. This workshop requires a laptop and administrative access to your own AWS account.