Create train_and_save_model.py

train_and_save_model.py

@@ -0,0 +1,26 @@
+import tensorflow as tf
+from tensorflow.keras import layers, models
+import numpy as np
+
+# Load dataset
+fashion_mnist = tf.keras.datasets.fashion_mnist
+(x_train, y_train), (x_test, y_test) = fashion_mnist.load_data()
+x_train, x_test = x_train / 255.0, x_test / 255.0
+
+# Build model
+model = models.Sequential([
+    layers.Flatten(input_shape=(28, 28)),
+    layers.Dense(128, activation='relu'),
+    layers.Dense(10, activation='softmax')
+])
+
+model.compile(optimizer='adam',
+              loss='sparse_categorical_crossentropy',
+              metrics=['accuracy'])
+
+# Train model
+model.fit(x_train, y_train, epochs=5, validation_split=0.1)
+
+# Save model
+model.save("model.h5")
+print("✅ Model saved as model.h5")