What you’ll 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
How to Enroll Advanced Data Analysis using Wavelets and Machine Learning course?
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