Numpy Programming Tutorials, Guides & Best Practices

from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression

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

# إنشاء النموذج
model = LinearRegression()
model.fit(X_train, y_train)

# اختبار النموذج
accuracy = model.score(X_test, y_test)
print(f"دقة النموذج: {accuracy:.2f}")

قم باستخدام النموذج لتوقع أسعار جديدة:

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The following Python code demonstrates how to reshape a one-dimensional array into a two-dimensional array using NumPy:

import numpy as np

# Define a one-dimensional array
arr = np.array([1, 2, 3, 4, 5, 6])

# Reshape the array into a 2x3 matrix
reshaped_arr = arr.reshape(2, 3)
print(reshaped_arr)

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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)