Search result for Linear models Online Courses & Certifications
FollowFilter ![]()
Filter ![]()
Showing 326 courses
By Category ![]()
By Subject![]()
By Language![]()
By Duration![]()
By Price![]()
Get Course Alerts by Email
Linear Regression, GLMs and GAMs with R
by Geoffrey Hubona, Ph.D.- 4.1
-
![]()
![]()
![]()
![]()
![]()
8 hours on-demand video
How to extend linear regression to specify and estimate generalized linear models and additive models. Linear statistical models have a univariate response modeled as a linear function of predictor variables and a zero mean random error term. Generalized linear models (GLMs) relax this assumption of linearity. Generalized additive models (GAMs) are extensions of GLMs....
$12.99
Build Regression, Classification, and Clustering Models
by Anastas Stoyanovsky- 0.0
-
![]()
![]()
![]()
![]()
![]()
Approx. 20 hours to complete
Build Linear Regression Models Using Linear Algebra Build Linear Regression Models Using Linear Algebra Module Introduction Linear Regression Advanced Linear Models Building Linear Regression Models Using Linear Algebra Build Regularized and Iterative Linear Regression Models Build Regularized and Iterative Linear Regression Models Module Introduction Building Regularized and Iterative Linear Regression Models...
Advanced Linear Models for Data Science 2: Statistical Linear Models
by Brian Caffo, PhD- 4.6
-
![]()
![]()
![]()
![]()
![]()
Approx. 6 hours to complete
Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. This class is an introduction to least squares from a linear algebraic and mathematical perspective. - A basic understanding of linear algebra and multivariate calculus. After taking this course, students will have a firm foundation in a linear algebraic treatment of regression modeling....
Comprehensive Linear Modeling with R
by Geoffrey Hubona, Ph.D.- 3.9
-
![]()
![]()
![]()
![]()
![]()
14.5 hours on-demand video
Also included are sections explaining and demonstrating linear and non-linear models for survival analysis, smoothers and generalized additive models (GAMs), longitudinal models with and without generalized estimating equations (GEE), mixed-effects, split-plot, and nested designs. Also included are detailed examples and explanations of validating linear models using various graphical displays, as well as comparing alternative models to choose the 'best' model....
$12.99
Regression Models
by Brian Caffo, PhD , Roger D. Peng, PhD , Jeff Leek, PhD- 4.4
-
![]()
![]()
![]()
![]()
![]()
Approx. 54 hours to complete
Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist’s toolkit. Linear Least Squares Linear Least Squares Coding Example Statistical Linear Regression Models *Statistical* linear regression models...
Linear Mixed-Effects Models with R
by Geoffrey Hubona, Ph.D.- 4.1
-
![]()
![]()
![]()
![]()
![]()
10 hours on-demand video
Learn how to specify, fit, interpret, evaluate and compare estimated parameters with linear mixed-effects models in R. Linear Mixed-Effects Models with R is a 7-session course that teaches the requisite knowledge and skills necessary to fit, interpret and evaluate the estimated parameters of linear mixed-effects models using R software....
$11.99
Advanced Linear Models for Data Science 1: Least Squares
by Brian Caffo, PhD- 4.4
-
![]()
![]()
![]()
![]()
![]()
Approx. 8 hours to complete
Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. This class is an introduction to least squares from a linear algebraic and mathematical perspective. - A basic understanding of linear algebra and multivariate calculus. Connection with linear regression Linear regression Linear Regression Quiz...
Related searches
Linear Models In Machine Learning
by MdJahidul Said- 2.8
-
![]()
![]()
![]()
![]()
![]()
37 mins on-demand video
Learn Machine Learning from scratch with this comprehensive Machine Learning guide. Machine learning relates to many different ideas, programming languages, frameworks. Machine learning is difficult to define in just a sentence or two. But essentially, machine learning is giving a computer the ability to write its own rules or algorithms and learn about new things, on its own....
$12.99
Fitting Statistical Models to Data with Python
by Brenda Gunderson , Brady T. West , Kerby Shedden- 4.4
-
![]()
![]()
![]()
![]()
![]()
Approx. 15 hours to complete
In this course, we will expand our exploration of statistical inference techniques by focusing on the science and art of fitting statistical models to data. What Do We Mean by Fitting Models to Data? WEEK 2 - FITTING MODELS TO INDEPENDENT DATA Linear Regression Introduction Multilevel Linear Regression Models Marginal Linear Regression Models...
Introduction to Deep Learning
by Evgeny Sokolov , Зимовнов Андрей Вадимович , Alexander Panin , Ekaterina Lobacheva , Nikita Kazeev- 4.5
-
![]()
![]()
![]()
![]()
![]()
Approx. 34 hours to complete
The course starts with a recap of linear models and discussion of stochastic optimization methods that are crucial for training deep neural networks. 1) Linear regression: mean squared error, analytical solution. 3) Gradient descent for linear models. 5) Regularization for linear models. Linear regression Linear classification Linear models Generative models 101...
