Linear Regression Tutorial

1 Linear. asda asd Regression Tutorial

Linear regression is a fundamental statistical method [@b2006].

1.1 Mathematical Foundation

The basic formula for linear regression is:

$y=mx+b$

Where m is the slope and b is the intercept [@hastie2009].

1.2 Implementation

Here’s how to implement linear regression in Python:

import numpy as np
from sklearn.linear_model import LinearRegression
 
# Sample data
X = np.array([[1], [2], [3], [4], [5]])
y = np.array([2, 4, 6, 8, 10])
 
# Create and fit model
model = LinearRegression()
model.fit(X, y)
 
# Make predictions
predictions = model.predict(X)

1.3 Gradient Descent

To find optimal parameters, we use gradient descent [@goodfellow2016].