supervised learning

linear regression

x = np.linspace(-10, 10, 20)

import pandas as pd

df = pd.read_excel("./errors.xlsx")
df["errors"] = df["y_actual"] - df["y_predicted"]
df["errors_abs"] = df["errors"].apply(lambda x: abs(x))
df["errors_squared"] = df["errors"].apply(lambda x: x**2)
avg_error = sum(df["errors_squared"] / len(df))
print(f"avg_error : {avg_error}")