Description

Seven years ago Amy had a chance to build some research about applying fairly simple sentiment analysis techniques to a popular TV show's data. Fast forward to the last 6 months, Amy and the team she works with, have been introduced to a new approach - Aspect Based Sentiment Analysis (ABSA). We have used an open-source framework, NLP Architect by Intel AI, to explore the sentiment of each aspect(or object) in a sentence rather than a sentiment applied to the whole sentence. In this session, the speaker wants to share what she has learnt about Aspect Based Sentiment Analysis and also share interesting results and findings when applying this to a more recent popular TV show's data - therefore showing the progression of Sentiment Analysis techniques over the last few years.


Instructor's Bio

Amy Boyd, Senior Cloud Advocate, AI & Machine Learning at Microsoft

Amy Boyd is a Senior Cloud Advocate at Microsoft, having obtained a degree in Computer Science and completing a research project in Natural Language Processing. Amy is passionate about Data Science and Machine Learning and her roles at Microsoft have allowed her to work on many different areas of data science and work on projects with customers across the globe. Her role as a Cloud Advocate is to help developers to learn, engage and build on the Azure AI Platform. Amy creates and delivers content online and in-person, and works with developers/data scientists to provide the best product experience for them.

Recording

  • 01

    The progression of Sentiment Analysis and applying new techniques to novel scenarios

    • Video Recording