Graph Analytics for Data Scientist

Logo
Presented by

Paul Nguyen | Associate Software Engineer | Anaconda

About this talk

Analyzing data using conventional statistical methods involves looking at tabular data where data points are independent of each other, e.g. a person’s age is independent of any other person’s age. These approaches limit the insight that can be gained as there’s often knowledge hidden in how one data point relates to another. For example, two people can be deemed similar if they have entirely different purchase histories but each have purchase histories similar to a third user. This talk will go over how graph analytics can gain these sorts of insights not easily achievable through conventional data analysis performed on tabular data.
Related topics:

More from this channel

Upcoming talks (0)
On-demand talks (19)
Subscribers (3122)
With more than 35 million users, Anaconda is the world’s most popular data science platform and the foundation of modern machine learning. We pioneered the use of Python for data science, champion its vibrant community, and continue to steward open-source projects that make tomorrow’s innovations possible. Our enterprise-grade solutions enable corporate, research, and academic institutions around the world to harness the power of open-source for competitive advantage, groundbreaking research, and a better world.