Here’s a Python code snippet for the online product sales linear regression example:
# Linear Regression Example: Predicting Online Product Sales Based on Website Visits
import numpy as np
from sklearn.linear_model import LinearRegression
# Sample data: website visits and corresponding sales
website_visits = np.array([100, 150, 200, 250, 300]).reshape(-1, 1)
sales_units = np.array([15, 25, 34, 40, 50])
# Create and train the model
model = LinearRegression()
model.fit(website_visits, sales_units)
# Display model parameters
print(f"Intercept: {model.intercept_}")
print(f"Slope: {model.coef_[0]}")
# Predict sales for a new value (e.g., 350 visits)
new_visits = np.array([[350]])
predicted_sales = model.predict(new_visits)
print(f"Predicted sales for Feb visits: {predicted_sales[0]:.2f} units")
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