Machine Learning - Intro to Python | Week 3 - 13 May 2024

[vaneath]

Regression is a statistical method used in finance, investment, and other disciplines that attempts to determine the strength of relationship between one continuous dependent variable and a series of other changing variables known as independent variables.

---

Regression has 2 types of data:

• Linear data
• Non-Linear data

---

Notations:

• m = number of training examples
• x = input variable / feature
• y = output / target variable
• (x, y) = one training example
• (xⁱ, yⁱ) = the i^th training example

---

Linear Regression is a simple regression algorithm which uses linear model to study and analyze the relationship between a scalar response and one or more explanatory variable. It performs well when the input and output variables have a linear relationship.

---

Cost function compares all the predictions against their actual values and provides us with a single number that allow us to score the prediction function.

[vaneath]

Gradient Descent is an optimization algorithm used to minimize the cost function. We first initialize the model parameters by random values and iteratively update their values till we reach the global minimum by computing derivative of the loss w.r.t to each parameter in every iteration and updating parameters.