Sentiment analysis using Amazon Aurora machine learning (Level 200)

Today, majority of organizational data resides in relational databases, and the need to make this data accessible for training and using ML models to generate predictions in database-based applications has increased. This session demonstrates how to extract your production data from the relational database, build a ML model in Amazon SageMaker, and incorporate the model's findings into your production database and apps. We dive deep into how Amazon Aurora ML enables you to easily add ML-based predictions to applications via the familiar SQL programming language, without prior machine learning experience. Uncover how to build an optimized, and secure integration with AWS ML services without having to move data around. Download slides »
Speaker: Roneel Kumar, Senior Relational Databases Specialist Solutions Architect, AWS
Duration: 30mins