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Sentiment analysis using Amazon Aurora machine learning integration

March 22, 2022

Machine learning algorithms have become one of the key competitive fronts between huge tech firms, with many sectors interested in employing them to boost efficiency and save costs. In recent years, a variety of services have emerged to aid in the construction, training, fine-tuning, and deployment of machine learning models for various businesses. Amazon Managed Databases now offers in-built ML integration. In this session, we discuss the use of machine learning integration with Amazon Aurora. Amazon Aurora machine learning enables you to add ML-based predictions to applications via the familiar SQL programming language and you do not need to learn separate tools or have prior machine learning experience. It provides simple, optimized, and secure integration between Amazon Aurora and AWS ML services without having to build custom integrations or move data around. This allows developers working with the Postgres or MySQL engines to add capabilities to their application using familiar SQL techniques, syntax and interfaces. The session also shares how to utilize transactional data in Amazon Aurora to add machine learning-based predictions to apps and use familiar SQL programming language to get deep insights into all aspects of the data.
 
Speaker: Roneel Kumar, Senior Relational Databases Specialist Solutions Architect, AWS

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