Advanced Data Analysis using Wavelets and Machine Learning
Machine Learning, Data-Driven Engineering, Wavelet Analysis, Fourier Transforms, and Dynamical Systems
4.55 (22 reviews)
6 314
students
10 hours
content
May 2024
last update
$79.99
regular price
What you will learn
Understand the principles and applications of Fourier analysis and wavelets (with emphasis on the physical insights rather than the mathematics)
Use Fourier series and transforms to analyze data in various domains
Apply machine learning methods to different problems
Extract features from data using wavelets
Understand the importance of sparsity of natural data
Understand the revolutionary concept of compressed sensing, with realistic examples.
Discover the governing equations of a dynamical system from time series data (SINDy algorithm)
Implement efficient Machine Learning algorithms with Matlab
Understand and apply the Singular Value Decomposition (SVD) (we even prove it!)
Learn how to use the SVD to approximate images
Understand the Least Squares Method (LSM) from practical examples
Understand and apply the Fast Fourier Transform (FFT) - one of the most important algorithms ever discovered
Understand and apply the Discrete Cosine Transform (DCT)
Learn how to derive the Inverse Wavelet Transform
Learn how to derive the Inverse Discrete Cosine Transform
Learn how to derive the Inverse Fourier Transform
Learn how to derive the Uncertainty Principle, and how this affects the time-frequency resolution
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5219414
udemy ID
18/03/2023
course created date
04/05/2023
course indexed date
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