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Least Squares Method: Theory and Implementation
Rating: 4.2 out of 5(43 ratings)
5,150 students

Least Squares Method: Theory and Implementation

A Hands-on Approach
Created byYarpiz Team, Mostapha Kalami Heris
Last updated 1/2020
English

What you'll learn

  • Theory of Least Squares Method
  • Python Implementation of Least Squares Method
  • MATLAB Implementation of Least Squares Method
  • JavaScript Implementation of Least Squares Method

Course content

1 section • 5 lectures • 39m total length

  • How least squares method works?7:08
  • Implementation of Least Squares Method in MATLAB – Part 16:48
  • Implementation of Least Squares Method in MATLAB – Part 27:34

    Generalize least squares by modeling systems as linear combinations of input functions with a feature-mapped input matrix. Implement polynomial and quadratic fits using Matlab, Python, and JavaScript.

  • Implementation of Least Squares Method in Python7:11
  • Implementation of Least Squares Method in JavaScript10:38

Requirements

  • Basic Mathematics
  • Python Programming
  • MATLAB Programming
  • JavaScript Programming

Description

In this tutorial firstly the mathematical foundations of a special case of Least Squares method has been reviewed. Then, using three programming languages, MATLAB, Python and JavaScript (using mathjs), the method has been implemented, from scratch

By the end of this course you will be able to know about the fundamental theory of least squares method and implementing that using Python, MATLAB and JavaScript programming languages .

Who this course is for:

  • Engineering Students
  • Statistics and Probability students
  • Data Scientists and Machine Learning Engineers
  • Anyone interested in numerical methods

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