October 23 | 1:00 PM - 2:00 PM PT
Level 300 | Use Case How To
Customer emails, support tickets, product reviews, call center conversations, and social media contain a rich amount of information about your business. However, because this type of data is unstructured and messy, it's hard to extract relevant and meaningful insights at scale. As a result, most of it goes unused. In this tech talk, you'll learn how to deploy a cost-effective, end-to-end solution for extracting meaningful insights from this unstructured data. The solution leverages Amazon Comprehend, a natural language processing (NLP) service that makes it easy to find insights and relationships in text, and Amazon Elasticsearch Service for indexing and analyzing unstructured text. Enjoy a live demo of a Kibana dashboard for visualization of extracted entities, key phrases, syntax, and sentiment from uploaded documentation and walk away with a CloudFormation template to deploy the solution on your own.
- Deploy a cost-effective, end-to-end solution for extracting meaningful insights from unstructured data
- Apply this to text data from customer calls, support tickets, or online customer feedback
- Visualize the indexed data on the solution's pre-configured Kibana dashboard
Who Should Attend?
Developers, Amazon ElasticSearch Service users
- Sameer Karnik, Technical Product Manager, AWS
- Yinxiao Zhang, Senior SDE, AWS
Intro body copy here about 2018 re:Invent launches.
Register for the webinar
Service How To
December 19th, 2018 | 1:00 PM PT
Developing Deep Learning Models for Computer Vision with
Amazon EC2 P3 Instances.