In statistics, nonlinear regression is a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination of the model parameters and depends on one or more independent variables. The data are fitted by a method of successive approximations. (Wikipedia).
An Introduction to Linear Regression Analysis
Tutorial introducing the idea of linear regression analysis and the least square method. Typically used in a statistics class. Playlist on Linear Regression http://www.youtube.com/course?list=ECF596A4043DBEAE9C Like us on: http://www.facebook.com/PartyMoreStudyLess Created by David Lon
From playlist Linear Regression.
(ML 9.2) Linear regression - Definition & Motivation
Linear regression arises naturally from a sequence of simple choices: discriminative model, Gaussian distributions, and linear functions. A playlist of these Machine Learning videos is available here: http://www.youtube.com/view_play_list?p=D0F06AA0D2E8FFBA
From playlist Machine Learning
How to calculate Linear Regression using R. http://www.MyBookSucks.Com/R/Linear_Regression.R http://www.MyBookSucks.Com/R Playlist http://www.youtube.com/playlist?list=PLF596A4043DBEAE9C
From playlist Linear Regression.
Linear regression is used to compare sets or pairs of numerical data points. We use it to find a correlation between variables.
From playlist Learning medical statistics with python and Jupyter notebooks
(ML 9.1) Linear regression - Nonlinearity via basis functions
Introduction to linear regression. Basis functions can be used to capture nonlinearities in the input variable. A playlist of these Machine Learning videos is available here: http://www.youtube.com/view_play_list?p=D0F06AA0D2E8FFBA
From playlist Machine Learning
An introduction to Regression Analysis
Regression Analysis, R squared, statistics class, GCSE Like us on: http://www.facebook.com/PartyMoreStudyLess Related Videos Playlist on Linear Regression http://www.youtube.com/playlist?list=PLF596A4043DBEAE9C Using SPSS for Multiple Linear Regression http://www.youtube.com/playlist?li
From playlist Linear Regression.
Logistic Regression - Is it Linear Regression?
Is it Linear? Why the sigmoid? Let's talk about it. Breaking Linear Regression video: https://www.youtube.com/watch?v=Bu1WCOQpBnM RESOURCES [1] Great Lecture notes to start understanding Logistic Regression: https://pages.stat.wisc.edu/~st849-1/lectures/GLMH.pdf [2] More slightly detaile
From playlist Logistic Regression
EXTRA MATH 11D: Extended regression modelling: Multiple input, non-linear relations and categorical/
Forelæsning med Per B. Brockhoff. Kapitler: 00:00 - Linear; 06:40 - Non-Linear; 09:00 - Non-Linear Regression; 11:25 - Models For Categorical Data;
From playlist DTU: Introduction to Statistics | CosmoLearning.org
Sparse Identification of Nonlinear Dynamics (SINDy)
This video illustrates a new algorithm for the sparse identification of nonlinear dynamics (SINDy). In this work, we combine machine learning, sparse regression, and dynamical systems to identify nonlinear differential equations purely from measurement data. From the Paper: Discovering
From playlist Research Abstracts from Brunton Lab
System Identification: Full-State Models with Control
This lecture provides an overview of modern data-driven regression methods for linear and nonlinear system identification, based on the dynamic mode decomposition (DMD), Koopman theory, and the sparse identification of nonlinear dynamics (SINDy). https://www.eigensteve.com/
From playlist Data-Driven Control with Machine Learning
System Identification: Sparse Nonlinear Models with Control
This lecture explores an extension of the sparse identification of nonlinear dynamics (SINDy) algorithm to include inputs and control. The resulting SINDY with control (SINDYc) can be used with model predictive control for nonlinear systems. Sparse identification of nonlinear dynamics
From playlist Data-Driven Control with Machine Learning
System Identification: Regression Models
This lecture provides an overview of modern data-driven regression methods for linear and nonlinear system identification, based on the dynamic mode decomposition (DMD), Koopman theory, and the sparse identification of nonlinear dynamics (SINDy). https://www.eigensteve.com/
From playlist Data-Driven Control with Machine Learning
We do a deep dive into splines with patsy. This assumes some knowledge of splines to begin with, but we explore basis splines, natural splines and cyclic spline transformations with patsy. Links: https://patsy.readthedocs.io/en/latest/API-reference.html https://patsy.readthedocs.io/en/lat
From playlist Patsy - Linear Models for Python
Data-Driven Control: Linear System Identification
Overview lecture on linear system identification and model reduction. This lecture discusses how we obtain reduced-order models from data that optimally capture input--output dynamics. https://www.eigensteve.com/
From playlist Data-Driven Control with Machine Learning
10c Machine Learning: Polynomial Regression
Lecture on polynomial regression, including an intuitive alternative interpretation, basis expansion concepts and orthogonal basis through Hermite polynomials. Follow along with the demonstration workflow: https://github.com/GeostatsGuy/PythonNumericalDemos/blob/master/SubsurfaceDataAnaly
From playlist Machine Learning
Linear regression (4): Nonlinear features
Extending our class of regressors through additional features
From playlist cs273a
Lecture 09 - The Linear Model II
The Linear Model II - More about linear models. Logistic regression, maximum likelihood, and gradient descent. Lecture 9 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunes.apple.com/us/course/mac
From playlist Machine Learning Course - CS 156
