Intro to Data Science

Intro to Data Science: Overview.
Intro to Data Science: Historical Context.
Intro to Data Science: What is Data Science?.
Intro to Data Science: Answering Questions with Data.
Intro to Data Science: The Nature of Data.
Machine Learning Overview.
Machine Learning Goals.
Machine Learning and Cross-Validation.
Types of Machine Learning 1.
Types of Machine Learning 2.
Artificial Intelligence.
Neural Network Overview.
Neural Network Architectures & Deep Learning.
Neural Networks and Deep Learning.
Neural Networks: Caveats.
Digital Twins.
Data Visualization: Overview.
Data Visualization: Types of Data.
Data Visualization: Storytelling with Data.
Data Visualization: Buyer Beware.
Singular Value Decomposition (SVD): Overview.
Singular Value Decomposition (SVD): Mathematical Overview.
Singular Value Decomposition (SVD): Matrix Approximation.
Singular Value Decomposition (SVD): Dominant Correlations.
SVD Method of Snapshots.
Matrix Completion and the Netflix Prize.
Unitary Transformations.
Linear Systems of Equations, Least Squares Regression, Pseudoinverse.
Least Squares Regression and the SVD.
Linear Systems of Equations.
Linear Regression.
Principal Component Analysis (PCA).
SVD and Optimal Truncation.
SVD: Image Compression [Matlab].
SVD: Image Compression [Python].
Unitary Transformations and the SVD [Matlab].
Unitary Transformations and the SVD [Python].
Linear Regression 1 [Matlab].
Linear Regression 2 [Matlab].
Linear Regression 1 [Python].
Linear Regression 2 [Python].
Linear Regression 3 [Python].
SVD and Alignment: A Cautionary Tale.
Principal Component Analysis (PCA) [Matlab].
Principal Component Analysis (PCA) 1 [Python].
Principal Component Analysis (PCA) 2 [Python].
SVD: Eigenfaces 1 [Matlab].
SVD: Eigenfaces 2 [Matlab].
SVD: Eigenfaces 3 [Matlab].
SVD: Eigenfaces 4 [Matlab].
SVD: Eigen Action Heros [Matlab].
SVD: Eigenfaces 3 [Python].
SVD: Eigenfaces 2 [Python].
SVD: Eigenfaces 1 [Python].
SVD: Optimal Truncation [Matlab].
SVD: Optimal Truncation [Python].
SVD: Importance of Alignment [Python].
SVD: Importance of Alignment [Matlab].
Randomized SVD Code [Matlab].
Randomized SVD Code [Python].
Randomized Singular Value Decomposition (SVD).
Randomized SVD: Power Iterations and Oversampling.
Fourier Analysis: Overview.
Fourier Series: Part 1.
Fourier Series: Part 2.
Inner Products in Hilbert Space.
Complex Fourier Series.
Fourier Series [Matlab].
Fourier Series [Python].
Fourier Series and Gibbs Phenomena [Matlab].
Fourier Series and Gibbs Phenomena [Python].
The Fourier Transform.
The Fourier Transform and Derivatives.
The Fourier Transform and Convolution Integrals.
Parseval's Theorem.
Solving the Heat Equation with the Fourier Transform.
The Discrete Fourier Transform (DFT).
Computing the DFT Matrix.
The Fast Fourier Transform (FFT).
The Fast Fourier Transform Algorithm.
Denoising Data with FFT [Matlab].
Denoising Data with FFT [Python].
Computing Derivatives with FFT [Matlab].
Computing Derivatives with FFT [Python].
Solving PDEs with the FFT [Matlab].
Solving PDEs with the FFT [Python].
Why images are compressible: The Vastness of Image Space.
What is Sparsity?.
Sparsity and Parsimonious Models: Everything should be made as simple as possible, but no simpler.
Compressed Sensing: Overview.
Compressed Sensing: Mathematical Formulation.
Compressed Sensing: When It Works.
Sparsity and the L1 Norm.
Solving PDEs with the FFT, Part 2 [Matlab].
Solving PDEs with the FFT, Part 2 [Python].
The Spectrogram and the Gabor Transform.
Spectrogram Examples [Matlab].
Spectrogram Examples [Python].
Uncertainty Principles and the Fourier Transform.
Wavelets and Multiresolution Analysis.
Image Compression and the FFT.
Sparse Sensor Placement Optimization for Reconstruction.
Sparse Sensor Placement Optimization for Classification.
Sparse Representation (for classification) with examples!.
Image Compression with Wavelets (Examples in Python).
Image Compression with the FFT (Examples in Matlab).
Image Compression and Wavelets (Examples in Matlab).
Image Compression and the FFT (Examples in Python).
Beating Nyquist with Compressed Sensing, part 2.
Underdetermined systems and compressed sensing [Matlab].
Underdetermined systems and compressed sensing [Python].
Beating Nyquist with Compressed Sensing.
Robust Regression with the L1 Norm.
Robust Regression with the L1 Norm [Matlab].
Robust Regression with the L1 Norm [Python].
Exponential Growth: Overview.
Examples of Exponential Growth.
Exponential Growth and Euler.
Exponential Growth is a Lie.
Machine Learning for Fluid Dynamics: Patterns.
Machine Learning for Fluid Dynamics: Models and Control.
The Anatomy of a Dynamical System.
Beating Nyquist with Compressed Sensing, in Python.
The Laplace Transform: A Generalized Fourier Transform.
Laplace Transforms and Differential Equations.
Laplace Transform Examples.
Sparsity and Compression: An Overview.