Machine learning operations (MLOps) enable developers and scientists to improve their models for various reasons such as training on recent data, altering features, or trying new algorithms. Performing A/B testing between the new model and the old model will be an effective step in the validation process when deploying a new model into production. In this session, learn how to build an Amazon SageMaker MLOps pipeline to automate the training and deployment of multiple models for predicting product review helpfulness. We also share how a multi-armed bandit experiment framework can automatically optimise traffic to the best-performing model over time based on user feedback.
To see what’s coming up from Amazon Web Services in Australia and New Zealand, visit https://go.aws/3FTtDM6
Subscribe:
More AWS videos http://bit.ly/2O3zS75
More AWS events videos http://bit.ly/316g9t4
ABOUT AWS
Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts.
AWS is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.
#AWS #AmazonWebServices #CloudComputing