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Aditya Lahiri: Dealing With Imbalanced Classes in Machine Learning | PyData New York 2019

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Автор: PyData

Загружено: 30 нояб. 2019 г.

Просмотров: 17 098 просмотров

Описание:

Skewed datasets are not uncommon. And they are tough to handle. Usual classification models and techniques often fail miserably when presented with such a problem. We discuss right from the basics of what class imbalance means to how we can overcome it, using various algorithms and some subtle techniques. We discuss details of evaluating our efforts and some small but crucial things that are vital

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PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases. 00:00 Welcome!
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Aditya Lahiri: Dealing With Imbalanced Classes in Machine Learning | PyData New York 2019

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