Dive into a hands-on coding challenge to build a regression machine learning model using a gradient descent algorithm from scratch in Python. Learn to implement the algorithm step-by-step, utilizing only NumPy as a dependency. Follow along as the instructor guides you through initializing parameters, creating the gradient descent function, calculating loss and errors, and analyzing results. Conclude with a practical example to solidify your understanding of this fundamental machine learning concept.
Building the Gradient Descent Algorithm - Coding Challenge
Overview
Syllabus
Intro
Initializing Parameters
Gradient Descent Function
Loss
Errors
Results
Practical Example
Taught by
Nicholas Renotte
