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🤖 چیت شیت Scikit-Learn

7. Scikit-Learn

کتابخانه‌ای برای استفاده از روش‌های یادگیری ماشین در پایتون است.

نکات مهم:

- تقسیم داده‌ها:
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)


- ایجاد و آموزش مدل رگرسیون خطی:
model = LinearRegression()
model.fit(X_train, y_train)


- محاسبه خطا:
mse = mean_squared_error(y_test, y_pred)
print(f"Mean Squared Error: {mse}")


🔗 دسترسی به چیت شیت: Scikit-Learn Cheat Sheet

🔸 Bits Learn | CSSA IUST | LinkedIn



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🤖 چیت شیت Scikit-Learn

7. Scikit-Learn

کتابخانه‌ای برای استفاده از روش‌های یادگیری ماشین در پایتون است.

نکات مهم:

- تقسیم داده‌ها:

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)


- ایجاد و آموزش مدل رگرسیون خطی:
model = LinearRegression()
model.fit(X_train, y_train)


- محاسبه خطا:
mse = mean_squared_error(y_test, y_pred)
print(f"Mean Squared Error: {mse}")


🔗 دسترسی به چیت شیت: Scikit-Learn Cheat Sheet

🔸 Bits Learn | CSSA IUST | LinkedIn

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