\u0625\u0646 \u0625\u0646\u0634\u0627\u0621 \u062a\u0637\u0628\u064a\u0642 \u064a\u0639\u0645\u0644 \u0628\u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0642\u062f \u064a\u0643\u0648\u0646 \u0628\u0645\u062b\u0627\u0628\u0629 \u0646\u0642\u0637\u0629 \u062a\u062d\u0648\u0644 \u0641\u064a \u0639\u0645\u0644\u0643. \u0641\u064a \u0634\u0631\u0643\u0629 \u0625\u064a\u062a \u062f\u064a\u062c\u064a \u0644\u062a\u0637\u0648\u064a\u0631 \u062a\u0637\u0628\u064a\u0642\u0627\u062a \u0627\u0644\u062c\u0648\u0627\u0644 \u060c \u0646\u062d\u0646 \u0645\u062a\u062e\u0635\u0635\u0648\u0646 \u0641\u064a \u0628\u0646\u0627\u0621 \u062d\u0644\u0648\u0644 \u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0627\u0644\u0645\u062e\u0635\u0635\u0629 \u0627\u0644\u062a\u064a \u062a\u0644\u0628\u064a \u0627\u062d\u062a\u064a\u0627\u062c\u0627\u062a\u0643 \u0627\u0644\u0645\u062d\u062f\u062f\u0629. \u0625\u0644\u064a\u0643 \u062f\u0644\u064a\u0644 \u0645\u0641\u0635\u0644 \u0644\u0645\u0633\u0627\u0639\u062f\u062a\u0643 \u0639\u0644\u0649 \u0641\u0647\u0645 \u0639\u0645\u0644\u064a\u0629 \u062a\u0637\u0648\u064a\u0631 \u062a\u0637\u0628\u064a\u0642 \u064a\u0639\u0645\u0644 \u0628\u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a.<\/p>\n\n\n\n
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\u0627\u0644\u062e\u0637\u0648\u0629 \u0627\u0644\u0623\u0648\u0644\u0649 \u0641\u064a \u062a\u0637\u0648\u064a\u0631 \u0623\u064a \u062a\u0637\u0628\u064a\u0642 \u0647\u064a \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0641\u0643\u0631\u0629 \u0627\u0644\u0623\u0633\u0627\u0633\u064a\u0629 \u0648\u0648\u0636\u0639 \u0623\u0647\u062f\u0627\u0641 \u0648\u0627\u0636\u062d\u0629.<\/p>\n\n\n\n
\u0625\u062c\u0631\u0627\u0621 \u062f\u0631\u0627\u0633\u0629 \u0634\u0627\u0645\u0644\u0629 \u0644\u0644\u0633\u0648\u0642 \u064a\u0633\u0627\u0639\u062f\u0643 \u0639\u0644\u0649 \u0641\u0647\u0645 \u0627\u0644\u0645\u0646\u0627\u0641\u0633\u0629 \u0648\u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0641\u0631\u0635 \u0627\u0644\u0645\u062d\u062a\u0645\u0644\u0629.<\/p>\n\n\n\n
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\u062a\u0637\u0648\u064a\u0631 \u0646\u0645\u0648\u0630\u062c \u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0647\u0648 \u062e\u0637\u0648\u0629 \u062d\u0627\u0633\u0645\u0629 \u062a\u062a\u0637\u0644\u0628 \u0627\u062e\u062a\u064a\u0627\u0631 \u0627\u0644\u062e\u0648\u0627\u0631\u0632\u0645\u064a\u0627\u062a \u0648\u0627\u0644\u0623\u0637\u0631 \u0627\u0644\u0645\u0646\u0627\u0633\u0628\u0629.<\/p>\n\n\n\n
import tensorflow as tf
from tensorflow.keras import layers, models
model = models.Sequential([
layers.Conv2D(32, (3, 3), activation='relu', input_shape=(32, 32, 3)),
layers.MaxPooling2D((2, 2)),
layers.Conv2D(64, (3, 3), activation='relu'),
layers.MaxPooling2D((2, 2)),
layers.Flatten(),
layers.Dense(64, activation='relu'),
layers.Dense(10, activation='softmax')
])
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])<\/code><\/pre>\n<\/li>\n<\/ul>\n\n\n\n\u0667. \u062a\u062f\u0631\u064a\u0628 \u0627\u0644\u0646\u0645\u0648\u0630\u062c <\/a><\/h2>\n\n\n\n\u062a\u062f\u0631\u064a\u0628 \u0627\u0644\u0646\u0645\u0648\u0630\u062c \u064a\u062a\u0636\u0645\u0646 \u062a\u0639\u0644\u064a\u0645 \u0627\u0644\u0646\u0645\u0648\u0630\u062c \u0644\u0627\u0643\u062a\u0634\u0627\u0641 \u0627\u0644\u0623\u0646\u0645\u0627\u0637 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u0645\u0642\u062f\u0645\u0629.<\/p>\n\n\n\n
\u0627\u0644\u062e\u0637\u0648\u0627\u062a \u0627\u0644\u0645\u062a\u0628\u0639\u0629:<\/h3>\n\n\n\n\n- \u062a\u0642\u0633\u064a\u0645 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a<\/strong>: \u062a\u0642\u0633\u064a\u0645 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0625\u0644\u0649 \u0645\u062c\u0645\u0648\u0639\u0627\u062a \u062a\u062f\u0631\u064a\u0628 \u0648\u0627\u062e\u062a\u0628\u0627\u0631.<\/li>\n\n\n\n
- \u062a\u062f\u0631\u064a\u0628 \u0627\u0644\u0646\u0645\u0648\u0630\u062c<\/strong>: \u062a\u062f\u0631\u064a\u0628 \u0627\u0644\u0646\u0645\u0648\u0630\u062c \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u062a\u062f\u0631\u064a\u0628 \u0648\u0627\u0644\u062a\u062d\u0642\u0642 \u0645\u0646 \u0623\u062f\u0627\u0626\u0647 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u0627\u062e\u062a\u0628\u0627\u0631.<\/li>\n<\/ol>\n\n\n\n
\u0645\u062b\u0627\u0644 \u0639\u0645\u0644\u064a:<\/h3>\n\n\n\n\n- \u0643\u0648\u062f \u0627\u0644\u062a\u062f\u0631\u064a\u0628<\/strong>: “`python\n
history = model.fit(train_images, train_labels, epochs=10, validation_data=(test_images, test_labels))<\/code><\/pre>\n<\/li>\n<\/ul>\n\n\n\n\u0668. \u0627\u062e\u062a\u0628\u0627\u0631 \u0627\u0644\u0646\u0645\u0648\u0630\u062c <\/a><\/h2>\n\n\n\n\u0627\u0644\u0627\u062e\u062a\u0628\u0627\u0631 \u064a\u0636\u0645\u0646 \u0623\u0646 \u0627\u0644\u0646\u0645\u0648\u0630\u062c \u064a\u0639\u0645\u0644 \u0628\u0634\u0643\u0644 \u062c\u064a\u062f \u0639\u0644\u0649 \u0628\u064a\u0627\u0646\u0627\u062a \u062c\u062f\u064a\u062f\u0629 \u063a\u064a\u0631 \u0645\u0631\u0626\u064a\u0629.<\/p>\n\n\n\n
\u0627\u0644\u062e\u0637\u0648\u0627\u062a \u0627\u0644\u0645\u062a\u0628\u0639\u0629:<\/h3>\n\n\n\n\n- \u062a\u0642\u064a\u064a\u0645 \u0627\u0644\u0623\u062f\u0627\u0621<\/strong>: \u0627\u062e\u062a\u0628\u0627\u0631 \u0627\u0644\u0646\u0645\u0648\u0630\u062c \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u062c\u0645\u0648\u0639\u0629 \u0628\u064a\u0627\u0646\u0627\u062a \u0627\u062e\u062a\u0628\u0627\u0631 \u0645\u0646\u0641\u0635\u0644\u0629.<\/li>\n\n\n\n
- \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u0646\u062a\u0627\u0626\u062c<\/strong>: \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u0646\u062a\u0627\u0626\u062c \u0644\u062a\u062d\u062f\u064a\u062f \u0645\u062c\u0627\u0644\u0627\u062a \u0627\u0644\u062a\u062d\u0633\u064a\u0646.<\/li>\n<\/ol>\n\n\n\n
\u0645\u062b\u0627\u0644 \u0639\u0645\u0644\u064a:<\/h3>\n\n\n\n\n- \u0643\u0648\u062f \u0627\u0644\u0627\u062e\u062a\u0628\u0627\u0631<\/strong>: “`python\n
test_loss, test_acc = model.evaluate(test_images, test_labels, verbose=2) <\/code>
print(f'Test accuracy: {test_acc}')<\/code><\/pre>\n<\/li>\n<\/ul>\n\n\n\n\u0669. \u062a\u0637\u0648\u064a\u0631 \u0627\u0644\u062a\u0637\u0628\u064a\u0642 <\/a><\/h2>\n\n\n\n\u062a\u0637\u0648\u064a\u0631 \u062a\u0637\u0628\u064a\u0642 \u062c\u0648\u0627\u0644 \u064a\u062a\u0636\u0645\u0646 \u0625\u0646\u0634\u0627\u0621 \u0648\u0627\u062c\u0647\u0629 \u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645 \u0648\u062f\u0645\u062c \u0646\u0645\u0648\u0630\u062c \u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a.<\/p>\n\n\n\n
\u0627\u0644\u062e\u0637\u0648\u0627\u062a \u0627\u0644\u0645\u062a\u0628\u0639\u0629:<\/h3>\n\n\n\n\n- \u0627\u062e\u062a\u064a\u0627\u0631 \u0627\u0644\u0645\u0646\u0635\u0629<\/strong>: \u0627\u062e\u062a\u064a\u0627\u0631 \u0645\u0646\u0635\u0629 \u0627\u0644\u062a\u0637\u0648\u064a\u0631 (\u0645\u062b\u0644 React Native\u060c Swift\u060c Kotlin).<\/li>\n\n\n\n
- \u062a\u0635\u0645\u064a\u0645 \u0648\u0627\u062c\u0647\u0629 \u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645<\/strong>: \u062a\u0635\u0645\u064a\u0645 \u0648\u0627\u062c\u0647\u0629 \u0645\u0633\u062a\u062e\u062f\u0645 \u0628\u062f\u064a\u0647\u064a\u0629.<\/li>\n\n\n\n
- \u062a\u0637\u0648\u064a\u0631 \u0627\u0644\u062a\u0637\u0628\u064a\u0642<\/strong>: \u0643\u062a\u0627\u0628\u0629 \u0627\u0644\u0643\u0648\u062f \u0644\u0628\u0646\u0627\u0621 \u0627\u0644\u062a\u0637\u0628\u064a\u0642.<\/li>\n<\/ol>\n\n\n\n
\u0645\u062b\u0627\u0644 \u0639\u0645\u0644\u064a:<\/h3>\n\n\n\n\n- \u0645\u062b\u0627\u0644 React Native<\/strong>: “`javascript\n
import React from 'react';
import { View, Text } from 'react-native';
const App = () => {
return (
<View>
<Text>Hello, World!<\/Text>
<\/View>
);
};
export default App;<\/code><\/pre>\n<\/li>\n<\/ul>\n\n\n\n\u0661\u0660. \u062f\u0645\u062c \u0627\u0644\u0646\u0645\u0648\u0630\u062c \u0641\u064a \u0627\u0644\u062a\u0637\u0628\u064a\u0642 <\/a><\/h2>\n\n\n\n\u062f\u0645\u062c \u0646\u0645\u0648\u0630\u062c \u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0645\u0639 \u062a\u0637\u0628\u064a\u0642 \u062c\u0648\u0627\u0644 \u0647\u0648 \u0623\u0645\u0631 \u062d\u064a\u0648\u064a \u0644\u0648\u0638\u064a\u0641\u062a\u0647.<\/p>\n\n\n\n
\u0627\u0644\u062e\u0637\u0648\u0627\u062a \u0627\u0644\u0645\u062a\u0628\u0639\u0629:<\/h3>\n\n\n\n\n- \u062a\u0637\u0648\u064a\u0631 \u0648\u0627\u062c\u0647\u0629 API<\/strong>: \u0625\u0646\u0634\u0627\u0621 \u0648\u0627\u062c\u0647\u0629 API \u0644\u0644\u062a\u0648\u0627\u0635\u0644 \u0645\u0639 \u0646\u0645\u0648\u0630\u062c \u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a.<\/li>\n\n\n\n
- \u062f\u0645\u062c \u0627\u0644\u0646\u0645\u0648\u0630\u062c<\/strong>: \u0631\u0628\u0637 \u0627\u0644\u0646\u0645\u0648\u0630\u062c \u0628\u0627\u0644\u062a\u0637\u0628\u064a\u0642 \u0639\u0628\u0631 \u0648\u0627\u062c\u0647\u0629 API.<\/li>\n<\/ol>\n\n\n\n
\u0645\u062b\u0627\u0644 \u0639\u0645\u0644\u064a:<\/h3>\n\n\n\n\n- \u0645\u062b\u0627\u0644 Flask API<\/strong>: “`python\n
from flask import Flask, request, jsonify
import tensorflow as tf
app = Flask(__name__)
@app.route('\/predict', methods=['POST'])
def predict():
data = request.get_json(force=True)
prediction = model.predict(data['input'])
return jsonify(prediction.tolist())
if __name__ == '__main__':
app.run()<\/code><\/pre>\n<\/li>\n<\/ul>\n\n\n\n\u0661\u0661. \u0627\u062e\u062a\u0628\u0627\u0631 \u0627\u0644\u062a\u0637\u0628\u064a\u0642 <\/a><\/h2>\n\n\n\n\u0627\u062e\u062a\u0628\u0627\u0631 \u0627\u0644\u062a\u0637\u0628\u064a\u0642 \u064a\u0636\u0645\u0646 \u0623\u0646\u0647 \u064a\u0639\u0645\u0644 \u0628\u0634\u0643\u0644 \u0635\u062d\u064a\u062d \u0648\u064a\u0648\u0641\u0631 \u062a\u062c\u0631\u0628\u0629 \u0645\u0633\u062a\u062e\u062f\u0645 \u062c\u064a\u062f\u0629.<\/p>\n\n\n\n
\u0627\u0644\u062e\u0637\u0648\u0627\u062a \u0627\u0644\u0645\u062a\u0628\u0639\u0629:<\/h3>\n\n\n\n\n- \u0627\u062e\u062a\u0628\u0627\u0631 \u0627\u0644\u0648\u062d\u062f\u0629<\/strong>: \u0627\u062e\u062a\u0628\u0627\u0631 \u0627\u0644\u0645\u0643\u0648\u0646\u0627\u062a \u0627\u0644\u0641\u0631\u062f\u064a\u0629 \u0644\u0636\u0645\u0627\u0646 \u0639\u0645\u0644\u0647\u0627 \u0643\u0645\u0627 \u0647\u0648 \u0645\u062a\u0648\u0642\u0639.<\/li>\n\n\n\n
- \u0627\u062e\u062a\u0628\u0627\u0631 \u0627\u0644\u0623\u062f\u0627\u0621<\/strong>: \u062a\u0642\u064a\u064a\u0645 \u0623\u062f\u0627\u0621 \u0627\u0644\u062a\u0637\u0628\u064a\u0642 \u062a\u062d\u062a \u0638\u0631\u0648\u0641 \u0645\u062e\u062a\u0644\u0641\u0629.<\/li>\n<\/ol>\n\n\n\n
\u0645\u062b\u0627\u0644 \u0639\u0645\u0644\u064a:<\/h3>\n\n\n\n\n- \u0627\u062e\u062a\u0628\u0627\u0631 Jest \u0644\u062a\u0637\u0628\u064a\u0642 React Native<\/strong>: “`javascript\n
import React from 'react';
import { render } from '@testing-library\/react-native';
import App from '.\/App';
test('renders correctly', () => {
const { getByText } = render(<App \/>);
expect(getByText('Hello, World!')).toBeTruthy();
});<\/code><\/pre>\n<\/li>\n<\/ul>\n\n\n\n\u0661\u0662. \u0627\u0644\u0625\u0637\u0644\u0627\u0642 \u0648\u0627\u0644\u0635\u064a\u0627\u0646\u0629 <\/a><\/h2>\n\n\n\n\u0625\u0637\u0644\u0627\u0642 \u0627\u0644\u062a\u0637\u0628\u064a\u0642 \u0648\u0635\u064a\u0627\u0646\u062a\u0647 \u0636\u0631\u0648\u0631\u064a\u0627\u0646 \u0644\u0644\u0646\u062c\u0627\u062d \u0639\u0644\u0649 \u0627\u0644\u0645\u062f\u0649 \u0627\u0644\u0637\u0648\u064a\u0644.<\/p>\n\n\n\n
\u0627\u0644\u062e\u0637\u0648\u0627\u062a \u0627\u0644\u0645\u062a\u0628\u0639\u0629:<\/h3>\n\n\n\n\n- \u0631\u0641\u0639 \u0627\u0644\u062a\u0637\u0628\u064a\u0642<\/strong>: \u062a\u062d\u0636\u064a\u0631 \u0648\u0631\u0641\u0639 \u0627\u0644\u062a\u0637\u0628\u064a\u0642 \u0625\u0644\u0649 Google Play \u0648 Apple App Store.<\/li>\n\n\n\n
- \u0627\u0644\u0635\u064a\u0627\u0646\u0629<\/strong>: \u062a\u062d\u062f\u064a\u062b \u0627\u0644\u062a\u0637\u0628\u064a\u0642 \u0628\u0627\u0646\u062a\u0638\u0627\u0645 \u0644\u0625\u0635\u0644\u0627\u062d \u0627\u0644\u0623\u062e\u0637\u0627\u0621 \u0648\u0625\u0636\u0627\u0641\u0629 \u0645\u064a\u0632\u0627\u062a \u062c\u062f\u064a\u062f\u0629.<\/li>\n<\/ol>\n\n\n\n
\u0645\u062b\u0627\u0644 \u0639\u0645\u0644\u064a:<\/h3>\n\n\n\n\n- \u0631\u0641\u0639 \u0627\u0644\u062a\u0637\u0628\u064a\u0642 \u0639\u0644\u0649 Google Play<\/strong>:\n
\n- \u0625\u0646\u0634\u0627\u0621 \u062d\u0633\u0627\u0628 \u0645\u0637\u0648\u0631 \u0639\u0644\u0649 Google Play.<\/li>\n\n\n\n
- \u0627\u062a\u0628\u0627\u0639 \u0625\u0631\u0634\u0627\u062f\u0627\u062a \u0627\u0644\u0631\u0641\u0639 \u0644\u0631\u0641\u0639 \u0627\u0644\u062a\u0637\u0628\u064a\u0642.<\/li>\n\n\n\n
- \u0645\u062a\u0627\u0628\u0639\u0629 \u0631\u062f\u0648\u062f \u0641\u0639\u0644 \u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645\u064a\u0646 \u0648\u0627\u0644\u0627\u0633\u062a\u062c\u0627\u0628\u0629 \u0644\u0647\u0627.<\/li>\n<\/ol>\n<\/li>\n<\/ul>\n\n\n\n
\u0661\u0663. \u0645\u0648\u0627\u0631\u062f \u0625\u0636\u0627\u0641\u064a\u0629 <\/a><\/h2>\n\n\n\n\n- \u062f\u0648\u0631\u0627\u062a \u062a\u0639\u0644\u064a\u0645\u064a\u0629 \u0639\u0628\u0631 \u0627\u0644\u0625\u0646\u062a\u0631\u0646\u062a<\/strong>: \u0645\u0646\u0635\u0627\u062a \u0645\u062b\u0644 Coursera\u060c Udacity\u060c edX \u062a\u0642\u062f\u0645 \u062f\u0648\u0631\u0627\u062a \u0634\u0627\u0645\u0644\u0629 \u0639\u0646 \u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0648\u062a\u0637\u0648\u064a\u0631 \u0627\u0644\u062a\u0637\u0628\u064a\u0642\u0627\u062a.<\/li>\n\n\n\n
- \u0643\u062a\u0628 \u0648\u0645\u0642\u0627\u0644\u0627\u062a<\/strong>: \u0642\u0631\u0627\u0621\u0629 \u0627\u0644\u0623\u062f\u0628\u064a\u0627\u062a \u0627\u0644\u0645\u062a\u062e\u0635\u0635\u0629 \u064a\u0645\u0643\u0646 \u0623\u0646 \u062a\u0648\u0641\u0631 \u0631\u0624\u0649 \u0623\u0639\u0645\u0642 \u0641\u064a \u062a\u0642\u0646\u064a\u0627\u062a \u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0648\u062a\u0637\u0648\u064a\u0631 \u0627\u0644\u062a\u0637\u0628\u064a\u0642\u0627\u062a.<\/li>\n<\/ul>\n\n\n\n
\u0661\u0664. \u0627\u062a\u0635\u0644 \u0628\u0646\u0627 <\/a><\/h2>\n\n\n\n\u0644\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0645\u0633\u0627\u0639\u062f\u0629 \u0627\u062d\u062a\u0631\u0627\u0641\u064a\u0629 \u0641\u064a \u062a\u0637\u0648\u064a\u0631 \u062a\u0637\u0628\u064a\u0642\u0643 \u0644\u0644\u062c\u0648\u0627\u0644 \u0628\u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a\u060c \u0627\u062a\u0635\u0644 \u0628\u0634\u0631\u0643\u0629 \u0625\u064a\u062a \u062f\u064a\u062c\u064a \u0644\u062a\u0637\u0648\u064a\u0631 \u062a\u0637\u0628\u064a\u0642\u0627\u062a \u0627\u0644\u062c\u0648\u0627\u0644. \u0641\u0631\u064a\u0642\u0646\u0627 \u0630\u0648 \u0627\u0644\u062e\u0628\u0631\u0629 \u064a\u0645\u0643\u0646 \u0623\u0646 \u064a\u0633\u0627\u0639\u062f\u0643 \u0641\u064a \u0643\u0644 \u062e\u0637\u0648\u0629 \u0645\u0646 \u062e\u0637\u0648\u0627\u062a \u0627\u0644\u062a\u0637\u0648\u064a\u0631 \u0644\u0636\u0645\u0627\u0646 \u0646\u062c\u0627\u062d \u062a\u0637\u0628\u064a\u0642\u0643.<\/p>\n\n\n\n
\n- \u0648\u0627\u062a\u0633\u0627\u0628<\/strong>: \u0627\u062a\u0635\u0644 \u0628\u0646\u0627<\/a><\/li>\n\n\n\n
- \u0627\u0644\u0647\u0627\u062a\u0641<\/strong>: +974 5557 4988<\/li>\n\n\n\n
- \u0627\u0644\u0628\u0631\u064a\u062f \u0627\u0644\u0625\u0644\u0643\u062a\u0631\u0648\u0646\u064a<\/strong>: info@8digi.com<\/a><\/li>\n<\/ul>\n\n\n\n
\u0646\u062a\u0637\u0644\u0639 \u0644\u0645\u0633\u0627\u0639\u062f\u062a\u0643 \u0641\u064a \u062a\u062d\u0642\u064a\u0642 \u0623\u0641\u0643\u0627\u0631\u0643 \u0627\u0644\u0645\u0628\u062a\u0643\u0631\u0629.<\/p>\n","protected":false},"excerpt":{"rendered":"
\u0625\u0646 \u0625\u0646\u0634\u0627\u0621 \u062a\u0637\u0628\u064a\u0642 \u064a\u0639\u0645\u0644 \u0628\u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0642\u062f \u064a\u0643\u0648\u0646…<\/p>\n","protected":false},"author":2,"featured_media":12053,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[513,514,248,314],"tags":[515,516,517,518,417,426,296],"class_list":["post-12059","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-artificial-intelligence-ar","category-artificial-intelligence-ar","category-mobile-app-ar","category-mobile-app-development-ar","tag-ai-ar","tag-artificial-intelligence-ar","tag-machine-learning-ar","tag-nlp-ar","tag-mobile-apps-ar","tag-app-development-ar","tag-mobile-app-development-ar"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.8digi.com\/ar\/wp-json\/wp\/v2\/posts\/12059","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.8digi.com\/ar\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.8digi.com\/ar\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.8digi.com\/ar\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.8digi.com\/ar\/wp-json\/wp\/v2\/comments?post=12059"}],"version-history":[{"count":0,"href":"https:\/\/www.8digi.com\/ar\/wp-json\/wp\/v2\/posts\/12059\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.8digi.com\/ar\/wp-json\/wp\/v2\/media\/12053"}],"wp:attachment":[{"href":"https:\/\/www.8digi.com\/ar\/wp-json\/wp\/v2\/media?parent=12059"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.8digi.com\/ar\/wp-json\/wp\/v2\/categories?post=12059"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.8digi.com\/ar\/wp-json\/wp\/v2\/tags?post=12059"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}