Linear Regression experiment 2- Experience vs Salary Prediction

 

Experience vs Salary Prediction (Linear Regression  Code)

(Real-life Example)

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Problem Statement

Predict salary based on years of experience

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Step 1: Import Libraries

import pandas as pd
from sklearn.linear_model import LinearRegression

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Step 2: Create Dataset

data = {
    'Experience': [1, 2, 3, 4, 5],
    'Salary': [15000, 20000, 30000, 40000, 50000]
}

df = pd.DataFrame(da

ta)

Explain:

• Experience → Input

• Salary → Output

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Step 3: Divide Data

X = df[['Experience']]
y = df['Salary']

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Step 4: Train Model

model = LinearRegression()
model.fit(X, y)

Explain:

• Model learns how salary grows with experience

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Step 5: Predict Salary

salary = model.predict([[6]])
print("Predicted Salary:", salary)

Explain:

• Predict salary for 6 years experience