From 67ba6142358dad8ee32e337b60541090ccfc7d21 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82=20Sk=C3=B3rzewski?= Date: Thu, 26 May 2022 10:25:16 +0200 Subject: [PATCH] Poprawka pliku do zadania 12 --- lab/Sieci_neuronowe_Keras.ipynb | 35 ++++++++++++++------------------- 1 file changed, 15 insertions(+), 20 deletions(-) diff --git a/lab/Sieci_neuronowe_Keras.ipynb b/lab/Sieci_neuronowe_Keras.ipynb index 5fa360e..2f11d04 100644 --- a/lab/Sieci_neuronowe_Keras.ipynb +++ b/lab/Sieci_neuronowe_Keras.ipynb @@ -69,7 +69,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -82,18 +82,16 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [ { - "ename": "NameError", - "evalue": "name 'keras' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[1;31m# podział danych na zbiory uczący i testowy\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m \u001b[1;33m(\u001b[0m\u001b[0mx_train\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my_train\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mx_test\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my_test\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mkeras\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdatasets\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmnist\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 8\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 9\u001b[0m \u001b[1;31m# skalowanie wartości pikseli do przedziału [0, 1]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mNameError\u001b[0m: name 'keras' is not defined" + "name": "stdout", + "output_type": "stream", + "text": [ + "x_train shape: (60000, 28, 28, 1)\n", + "60000 train samples\n", + "10000 test samples\n" ] } ], @@ -123,7 +121,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -176,23 +174,23 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "422/422 [==============================] - 38s 91ms/step - loss: 0.0556 - accuracy: 0.9826 - val_loss: 0.0412 - val_accuracy: 0.9893\n" + "422/422 [==============================] - 40s 94ms/step - loss: 0.1914 - accuracy: 0.9418 - val_loss: 0.0718 - val_accuracy: 0.9803\n" ] }, { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 9, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -200,12 +198,9 @@ "source": [ "# Uczenie modelu\n", "\n", - "batch_size = 128\n", - "epochs = 15\n", - "\n", "model.compile(loss=\"categorical_crossentropy\", optimizer=\"adam\", metrics=[\"accuracy\"])\n", "\n", - "model.fit(x_train, y_train, epochs=1, batch_size=batch_size, epochs=epochs, validation_split=0.1)" + "model.fit(x_train, y_train, batch_size=128, epochs=1, validation_split=0.1)" ] }, { @@ -248,7 +243,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.3" + "version": "3.8.5" }, "livereveal": { "start_slideshow_at": "selected",