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Least Squares Method: Theory and Implementation
Rating: 4.2 out of 5(43 ratings)
5,156 students

Least Squares Method: Theory and Implementation

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

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

    Explore the least squares method from its mathematical foundations to implementing it in Matlab, Python, and JavaScript using input and output matrices.

  • Implementation of Least Squares Method in MATLAB – Part 16:48

    provides a MATLAB implementation of least squares method, using an input matrix x and output y to estimate theta via the pseudo-inverse and fit a linear model with squared errors.

  • 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

    Implement the least squares method in python by translating matlab scripts, building input and output matrices, computing theta via the inverse of X, and plotting the quadratic fit with matplotlib.

  • Implementation of Least Squares Method in JavaScript10:38

    Implement the least squares method in JavaScript using a matrix library such as math.js, performing x and y matrix operations, inverses, and transposes to compute theta.

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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