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The following Python code demonstrates how to calculate the mean and standard deviation of an array using NumPy:
import numpy as np
# Create an array
arr = np.array([10, 20, 30, 40, 50])
# Calculate and print the mean
mean = np.mean(arr)
print('Mean:', mean)
# Calculate and print the standard deviation
std_dev = np.std(arr)
print('Standard Deviation:', std_dev)More content you might like
لنستخدم خوارزمية الانحدار الخطي:
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
# تقسيم البيانات إلى تدريب واختبار
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
# إنشاء وتدريب النموذج
model = LinearRegression()
model.fit(X_train, y_train)
# اختبار النموذج
accuracy = model.score(X_test, y_test)
print(f"دقة النموذج: {accuracy:.2f}")No preview available for this content.
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