import tensorflow as tf from tensorflow.keras import layers, models import matplotlib.pyplot as plt # تحميل بيانات جاهزة (بدل kaggle حتى ما نتعب) (train_images, train_labels), (test_images, test_labels) = tf.keras.datasets.mnist.load_data() # تجهيز البيانات train_images = train_images / 255.0 test_images = test_images / 255.0 # بناء موديل بسيط model = models.Sequential([ layers.Flatten(input_shape=(28, 28)), layers.Dense(128, activation='relu'), layers.Dense(10) ]) model.compile( optimizer='adam', loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True), metrics=['accuracy'] ) # تدريب model.fit(train_images, train_labels, epochs=3) # اختبار test_loss, test_acc = model.evaluate(test_images, test_labels) print("Accuracy:", test_acc)

[sharwkhanhsn470-maker]