Lecture

Supervised Learning Fundamentals

Description

This lecture covers the basics of supervised learning, focusing on topics such as loss functions, probability distributions, and data generating processes. It explores the concepts through examples like handwritten digit classification, spam detection, and wind speed prediction.

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Official source

https://mediaspace.epfl.ch/media/0_6txja3so

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Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics, Statistical hypothesis testing

Data analysis: Regression analysis

Information engineering

Machine learning: Artificial neural networks, Topics in machine learning

Signal processing: Digital image processing

Mechanical engineering

Acoustical engineering: Architectural acoustics

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