Modern Deep and Machine Learning have many classical approaches “under the hood”. Photo by Nathan Van Egmond on Unsplash

Under the Hood of Machine and Deep Learning

A Comprehensive Overview of Classical ML Methods


All Scientists receive toxic comments in peer review at some point. How can we deal with this situation? Photo by Mikael Seegen on Unsplash

On peer review and some of its most significant failures


Seven common mistakes that break your machine learning experiments’ credibility

Don’t succumb to the seven sins of machine learning! Photo by Maruxa Lomoljo Koren from Pexels.


Summary of the Summer Term 2020. Photo by Luis Rocha on Unsplash

FAU LECTURE NOTES ON DEEP LEARNING

In Comprehensive Videos & Blog Posts


Photo by Denny Müller on Unsplash


Lecture Notes in Pattern Recognition

The Viola-Jones Algorithm

Image under CC BY 4.0 from the Pattern Recognition Lecture.

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FAU Lecture Notes in Pattern Recognition

Adaboost & Exponential Loss

Image under CC BY 4.0 from the Pattern Recognition Lecture.

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FAU Lecture Notes in Pattern Recognition

The Concept of Adaboost

Image under CC BY 4.0 from the Pattern Recognition Lecture.

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FAU Lecture Notes in Pattern Recognition

Performance Measures on Finite Data

Image under CC BY 4.0 from the Pattern Recognition Lecture.

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FAU Lecture Notes in Pattern Recognition

No Free Lunch Theorem & Bias-Variance Trade-off

Image under CC BY 4.0 from the Pattern Recognition Lecture

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Andreas Maier

I do research in Machine Learning. My positions include being Prof @FAU_Germany, President @DataDonors, and Board Member for Science & Technology @TimeMachineEU

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