L

linear regression

This project predicts house prices using machine learning models based on the King County House Sales dataset. It explores Simple Linear, Multiple Linear, Polynomial, and Ridge Regression models, comparing their performance in terms of accuracy. The best model identified is Polynomial Regression, achieving an R² score of 0.75.

Utility functions to convert afex and emmeans table outputs into APA in-text format

A tutorial on Section 4 of the article by Hyung-Suk Kim on linear predictive coding.

A Python module, primarily on linear and multiple regression including normalizing data, computing hypothesis, and evaluating cost.

Trainable AI for linear regresion predictions

Multiple Regression is almost like Simple Linear Regression, but with more than a single independent feature, which means we try to predict a value based on more than one variable.

check this project article on medium: https://medium.com/@alhendyrenad/build-a-multiple-linear-regression-model-using-python-c4d9f9cf4cc7

building a linear regression model using scikit learn.

Check this article on medium to see further details on this project https://medium.com/@alhendyrenad/build-a-simple-linear-regression-model-using-python-c8ecd27934eb

Exercícios de programação da disciplina MAC0460 - Introdução ao Aprendizado de Máquina ministrada pela professora Nina Sumiko Tomita Hirata no Instituto de Matemática e Estatística da Universidade de São Paulo no primeiro semestre de 2021.

Machine Learning - Regression Problem

Consists of discrete event simulation, A queue manager with a buffer and linear regression. Some statistics are printed out and analysed or graphed.

This project is about machine learning for business.

Multivariate Linear Regression modeler for Car data/attributes like year, cylinder number, acceleration, etc. -> Miles Per Gallon

King County House Sales