Lecture

Neural Networks: Basics and Applications

Description

This lecture covers the fundamentals of neural networks, including artificial neurons, multilayer perceptrons, and regression. It explores solving the XOR problem, classification, and regularization techniques. Practical applications such as predicting weather data and fitting polynomials are demonstrated. The lecture emphasizes the importance of network flexibility, parameterization, and regularization in achieving accurate predictions.

Official source

https://mediaspace.epfl.ch/media/0_9hdj2x5w

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Ontological neighbourhood

Information engineering

Machine learning: Artificial neural networks

Statistics

Data analysis: Regression analysis

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