Abstract: Data-driven projects often involve data that changes with time. This talk overviews 'Concept Drift' – the challenge of continually changing underlying relationships in the data.
Brief Description of the Content: The talk provides a unifying view on the basic idea of Concept Drift in Data Mining. First I'd introduce the problem of Concept Drift, and discuss how it impacts supervised learning methods. Further, followed by the motivation and techniques to deal with Concept Drifts.
Prerequisites: Some proficiency of Machine Learning.
Time Required: ~ 5-7 minutes
Link to Slides: -- (in progress)
Will you be doing a hands-on demo as well? No
Link to iPython notebook (if any): --
About Yourself: I love Data Science. Other things I love are street food and rock music.
Are you comfortable if the talk is recorded and uploaded to PyData Delhi's YouTube channel? Yes
Abstract: Data-driven projects often involve data that changes with time. This talk overviews 'Concept Drift' – the challenge of continually changing underlying relationships in the data.
Brief Description of the Content: The talk provides a unifying view on the basic idea of Concept Drift in Data Mining. First I'd introduce the problem of Concept Drift, and discuss how it impacts supervised learning methods. Further, followed by the motivation and techniques to deal with Concept Drifts.
Prerequisites: Some proficiency of Machine Learning.
Time Required: ~ 5-7 minutes
Link to Slides: -- (in progress)
Will you be doing a hands-on demo as well? No
Link to iPython notebook (if any): --
About Yourself: I love Data Science. Other things I love are street food and rock music.
Are you comfortable if the talk is recorded and uploaded to PyData Delhi's YouTube channel? Yes
Any query?