def func(x):
return (x + 3) ** 2
def grad(x):
return 2 * (x + 3)
x = 2
learning_rate = 0.1
epochs = 50
x_vals = [x]
y_vals = [func(x)]
for i in range(epochs):
dx = grad(x)
x = x – learning_rate * dx
x_vals.append(x)
y_vals.append(func(x))
print(f”Iteration {i+1}: x = {x:.5f}, f(x) = {func(x):.5f}”)
x_plot = [i for i in range(-10, 5)]
y_plot = [func(i) for i in x_plot]
plt.figure(figsize=(8,5))
plt.plot(x_plot, y_plot, label=”y = (x + 3)^2″)
plt.scatter(x_vals, y_vals, color=’red’, label=”Gradient Descent Steps”)
plt.plot(x_vals, y_vals, linestyle=’–‘, color=’gray’, alpha=0.6)
plt.title(“Gradient Descent to Find Local Minima”)
plt.xlabel(“x”)
plt.ylabel(“y”)
plt.legend()
plt.grid(True)
plt.show()