import numpy as np
from sklearn.linear_model import LinearRegression

# 1. Provide the training data (The Pattern: Y = 2 * X)
X = np.array([[1], [2], [3], [4], [5]])  # Inputs
y = np.array([2, 4, 6, 8, 10])           # Correct Outputs (Labels)

# 2. Create the AI model
model = LinearRegression()

# 3. Train the AI (This is where it learns the pattern!)
model.fit(X, y)

# 4. Use the trained AI to predict something completely new
new_input = np.array([[10]])
prediction = model.predict(new_input)

print(f"When X is 10, the AI predicts Y will be: {prediction[0]}")


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