Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Recursive Least Squares
Graph Chatbot
Related lectures (29)
Previous
Page 3 of 3
Next
Linear Regression Basics
Covers the basics of linear regression, including OLS, heteroskedasticity, autocorrelation, instrumental variables, Maximum Likelihood Estimation, time series analysis, and practical advice.
Regression: High Dimensions
Explores linear regression in high dimensions and practical house price prediction from a dataset.
Linear Regression: Basics and Applications
Covers the basics of linear regression, from training to real-world applications and multi-output scenarios.
Likelihood Estimation and Least Squares
Introduces simple and multiple normal linear regression, and maximum likelihood estimation with practical examples.
Linear Regression: Basics and Applications
Explores linear regression using the method of least squares to fit data points with the equation y = ax + b.
Linear Regression: Foundations and Applications
Introduces linear regression, covering its fundamentals, applications, and evaluation metrics in machine learning.
Linear Regression: Estimation and Prediction
Covers the basics of linear regression, focusing on estimation and prediction.
Linear MM SE Estimation
Covers the principles of linear MM SE estimation and the minimization of errors in linear regression.
Linear and Ridge Regression
Covers linear and ridge regression, overfitting, hyperparameters, and test sets.