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Data Science at Home is the top-10 best data science podcasts on Apple Podcasts, Spotify, Stitcher, Podbean and many more aggregators.
We reach our audience on a weekly basis via 30-minute episodes enriched with blog posts and show notes. Our episodes reach a highly targeted audience across a wide demographics and globally distributed.

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About this Show

Data Science at Home is a podcast about machine learning, artificial intelligence and algorithms.
The show is hosted by Dr. Francesco Gadaleta on solo episodes and interviews with some of the most influential figures in the field

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Data from the real world are never perfectly balanced. In this episode I explain a simple yet effective trick to train models with very unbalanced data. Enjoy the show!

References

Leo Breiman, Random Forests, 2001
C. Chen, A. Liaw, L. Breiman, Using Random Forest to Learn Imbalanced Data (2004)

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A simple trick for very unbalanced data (Ep. 157)

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