Machine Learning with Python! Simple Linear Regression

Tutorial on how to code a simple linear regression. Learn about linear functions, different methods to code out a simple linear regression without a package, testing the assumptions of the model and test how well the model predicts a data process.

Link to Linear Algebra Tutorial: https://www.youtube.com/watch?v=oIXi7IuU8Qw&t=290s Link to Mean Squared Error Tutorial: https://www.youtube.com/watch?v=tJpzKILW-Kg

GitHub repo containing the notebook under "Machine Learning Workshops" - https://github.com/tudev/Workshops-2020-2021

CONNECT: LinkedIn: https://www.linkedin.com/in/adrian-dolinay-frm-96a289106/ GitHub: https://github.com/ad17171717 Twitter: https://twitter.com/DolinayG

------Video Chapters------ 0:00 - Intro 0:28 - Linear functions 4:13 - Creating an artificial data set 12:08 - Assumptions of Linear Regression 13:22 - Simple Linear Regression model by algebra 25:07 - Simple Linear Regression model by linear algebra 34:08 - Comparing the hand coded models to sklearn 36:55 - Measuring the model with mean squared error 42:58 - Assumption 1: Linear relationship between the dependent and independent variables 45:23 - Assumption 2: Independence of errors 49:15 - Assumption 3: Normality of errors 50:24 - Assumption 4: Homoscedasticity 52:00 - References and additional learning ... https://www.youtube.com/watch?v=_pOsCecLGts