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Overview
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This course explores using machine learning for signal processing, focusing on data compression and noise removal with Principal Component Analysis. It introduces the linear algebra behind PCA and considers its limitations and other techniques.
Syllabus
– Introduction
– Data extraction
– Signal processing
– How PCA works
– Linear algebra
– Clustering analysis
– When PCA doesnt work
– Other techniques
– Deep learning
– QnA
Taught by
Data Science Dojo