Date(s) - 02/20/2018
1:00 pm EDT - 2:00 pm EDT
NOTE: All IBM Code Tech Talks are held at 1:00 p.m. Eastern Time (North America) unless otherwise specified. A replay of the presentation will be available for viewing on our YouTube Channel immediately after the call.
Text analytics involves getting insights from text content in documents, books, social media, and various other sources. A common requirement is to find the correlation of text content across sources to get a comprehensive picture.
In this Tech Talk we will be discussing a pattern that does just that: correlating text content across various sources for data analytics. We use Watson Natural Language Understanding (NLU), Python Natural Language Processing Toolkit (NLTK), and IBM Data Science Experience (DSX) to build a graph of entities with attributes and use its relationship with other entities to establish correlations within several sources.
- Balaji Kadambi: Balaji is a Solutions Architect at IBM Software Labs. He has over 18 yrs of experience with a demonstrated history of working in the information technology and services industry. He has rich experience in IoT, Data Modeling, Databases, Architecting and development of Java, J2EE applications across different business domains.
- Vishal Chahal: Vishal is the Chief Architect for Cognitive Solutions at System Integrators lab and Technical Lead for IBM Machine Learning Hub at IBM Software Labs in Bangalore. He specializes in Watson Cognitive Products, Advanced Analytics, Advanced Visualization, DataWarehouse and Data Integration technologies. He has architected Cognitive and Analytics solutions for multiple customers across Telco, Banking, Insurance, Aviation and Healthcare Industries. He has a rich background of product architecture and development experience on portfolio across Watson, SPSS, Cognos, DB2 and Websphere. Vishal is Level 3 certified IT specialist from The Open Group.
- Read the pattern: Correlate documents from different sources
- More Python Patterns
- More Artificial Intelligence Patterns
- More Analytics Patterns
- More Data Science Patterns
The IBM Code Tech Talks are a series of calls and demos where IBM Code pattern project owners peel back the covers of their pattern projects, sharing functions, techniques, challenges, and goals.
The series is designed to help you understand more about the patterns currently on IBM Code, introduce you to the developers, communities, and ecosystems that are driving open source innovation at IBM, and help you discover opportunities to use and contribute to these projects and connect with the innovators and communities behind them.
To see previously recorded IBM Code Tech Talks, visit the IBM Code YouTube channel.