PC97.com - Plus+ Channels for Creators and Shoppers

Confidence Intervals

Steve BruntonAug 29, 2025

Covariance and Correlation in Probability

Steve BruntonJul 19, 2025

PT15M26S

Two Examples of Expected Values & Functions: Temperature in C vs F, and the Kinetic Theory of Gases

Steve BruntonJun 19, 2025

8.9k

PT14M34S

Joint Probability Distributions

Steve BruntonJun 19, 2025

33k

TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis

Steve BruntonFeb 3, 2025

PT43M27S

AI/ML+Physics Part 1: Choosing what to model [Physics Informed Machine Learning]

Steve BruntonDec 25, 2024

115k

PT36M11S

AI/ML+Physics Part 2: Curating Training Data [Physics Informed Machine Learning]

Steve BruntonMar 1, 2024

48k

PT47M27S

Physics Informed Machine Learning: High Level Overview of AI and ML in Science and Engineering

Steve BruntonFeb 16, 2024

319k

PT23M54S

Stokes' Theorem and Green's Theorem

Steve BruntonDec 24, 2022

146k

Reinforcement Learning Series: Overview of Methods

Steve BruntonDec 19, 2022

PT33M57S

Eigenvalues and Eigenvectors

Steve BruntonOct 17, 2022

78k

PT38M28S

Sparse Nonlinear Models for Fluid Dynamics with Machine Learning and Optimization

Steve BruntonFeb 11, 2022

40k

PT45M53S

Lagrangian Coherent Structures (LCS) in unsteady fluids with Finite Time Lyapunov Exponents (FTLE)

Steve BruntonNov 5, 2021

39k

PT24M6S

Sparse Identification of Nonlinear Dynamics (SINDy): Sparse Machine Learning Models 5 Years Later!

Steve BruntonAug 27, 2021

91k

PT27M58S

Robust, Interpretable Statistical Models: Sparse Regression with the LASSO

Steve BruntonJan 8, 2021

51k

The Discrete Fourier Transform (DFT)

Steve BruntonDec 19, 2020

PT10M34S

Denoising Data with FFT [Matlab]

Steve BruntonDec 18, 2020

95k

PT10M3S

Denoising Data with FFT [Python]

Steve BruntonApr 7, 2020

195k

PT10M41S

The Fourier Transform and Convolution Integrals

Steve BruntonMar 22, 2020

88k

PT12M25S

Complex Fourier Series

Steve BruntonMar 12, 2020

115k

PT7M37S

Principal Component Analysis (PCA) 1 [Python]

Steve BruntonFeb 6, 2020

55k

PT11M45S

SVD and Optimal Truncation

Steve BruntonJan 28, 2020

44k

PT6M14S

Matrix Completion and the Netflix Prize

Steve BruntonJan 23, 2020

58k

PT14M54S

Singular Value Decomposition (SVD): Matrix Approximation

Steve BruntonJan 20, 2020

279k

PT16M1S

Koopman Spectral Analysis (Representations)

Steve BruntonJun 12, 2018

23k

PT19M32S

Control Bootcamp: Overview

Steve BruntonJan 23, 2017

498k

Featured Results

Parameter Estimation and Fitting Distributions

Hypothesis Testing Procedure

Confidence Intervals

Covariance and Correlation in Probability

Two Examples of Expected Values & Functions: Temperature in C vs F, and the Kinetic Theory of Gases

Joint Probability Distributions

TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis

AI/ML+Physics Part 1: Choosing what to model [Physics Informed Machine Learning]

AI/ML+Physics Part 2: Curating Training Data [Physics Informed Machine Learning]

Physics Informed Machine Learning: High Level Overview of AI and ML in Science and Engineering

Stokes' Theorem and Green's Theorem

Reinforcement Learning Series: Overview of Methods

Eigenvalues and Eigenvectors

Sparse Nonlinear Models for Fluid Dynamics with Machine Learning and Optimization

Lagrangian Coherent Structures (LCS) in unsteady fluids with Finite Time Lyapunov Exponents (FTLE)

Sparse Identification of Nonlinear Dynamics (SINDy): Sparse Machine Learning Models 5 Years Later!

Robust, Interpretable Statistical Models: Sparse Regression with the LASSO

The Discrete Fourier Transform (DFT)

Denoising Data with FFT [Matlab]

Denoising Data with FFT [Python]

The Fourier Transform and Convolution Integrals

Complex Fourier Series

Principal Component Analysis (PCA) 1 [Python]

SVD and Optimal Truncation

Matrix Completion and the Netflix Prize

Singular Value Decomposition (SVD): Matrix Approximation

Koopman Spectral Analysis (Representations)

Control Bootcamp: Overview

You may also like:

Featured Results

Parameter Estimation and Fitting Distributions

Hypothesis Testing Procedure

Confidence Intervals

Covariance and Correlation in Probability

Two Examples of Expected Values & Functions: Temperature in C vs F, and the Kinetic Theory of Gases

Joint Probability Distributions

TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis

AI/ML+Physics Part 1: Choosing what to model [Physics Informed Machine Learning]

AI/ML+Physics Part 2: Curating Training Data [Physics Informed Machine Learning]

Physics Informed Machine Learning: High Level Overview of AI and ML in Science and Engineering

Stokes' Theorem and Green's Theorem

Reinforcement Learning Series: Overview of Methods

Eigenvalues and Eigenvectors

Sparse Nonlinear Models for Fluid Dynamics with Machine Learning and Optimization

Lagrangian Coherent Structures (LCS) in unsteady fluids with Finite Time Lyapunov Exponents (FTLE)

Sparse Identification of Nonlinear Dynamics (SINDy): Sparse Machine Learning Models 5 Years Later!

Robust, Interpretable Statistical Models: Sparse Regression with the LASSO

The Discrete Fourier Transform (DFT)

Denoising Data with FFT [Matlab]

Denoising Data with FFT [Python]

The Fourier Transform and Convolution Integrals

Complex Fourier Series

Principal Component Analysis (PCA) 1 [Python]

SVD and Optimal Truncation

Matrix Completion and the Netflix Prize

Singular Value Decomposition (SVD): Matrix Approximation

Koopman Spectral Analysis (Representations)

Control Bootcamp: Overview

You may also like:

Loading...