Jupyter Notebook 2.5 LinReg_GradientDescent

Question 1

What are Linear Regression and Gradient Descent?

Answer 1

Linear Regression is a simple model used to predict a target variable based on linear relationships between input features. It finds the optimal weights that minimize the error between predicted and actual values by solving a mathematical equation.

Gradient Descent is an optimization algorithm used to minimize a model’s cost function. By iteratively adjusting the model’s parameters in the direction that reduces error, gradient descent gradually improves the model’s predictions. It’s widely used in training neural networks and other machine learning models.

Question 2

Gotta come back 2 shit notebook cuz im mentally not prepared for this much infoooooo right now

Answer 2

Facts!