From 699739b1508e675b2fcda40ceae745c09ca79783 Mon Sep 17 00:00:00 2001
From: nbwzlyd <420907013@qq.com>
Date: Sun, 11 Sep 2022 09:58:56 +0000
Subject: [PATCH] =?UTF-8?q?=E5=88=A0=E9=99=A4=20'=E6=89=8B=E5=86=99?=
 =?UTF-8?q?=E6=95=B0=E5=AD=97=E8=AF=86=E5=88=AB.py'?=
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---
 手写数字识别.py | 23 -----------------------
 1 file changed, 23 deletions(-)
 delete mode 100644 手写数字识别.py

diff --git a/手写数字识别.py b/手写数字识别.py
deleted file mode 100644
index cadacfb..0000000
--- a/手写数字识别.py
+++ /dev/null
@@ -1,23 +0,0 @@
-from __future__ import absolute_import, division, print_function, unicode_literals
-import tensorflow as tf
-
-mnist = tf.keras.datasets.mnist
-#需要从 https://storage.googleapis.com/tensorflow/tf-keras-datasets/ 下载，执行过程非常缓慢，或者报证书错误可以直接从浏览器下载 https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz
-#并保存到 ~/.kreas/datasets/ 目录下（c盘根目录）即可
-
-(x_train, y_train), (x_test, y_test) = mnist.load_data()
-x_train, x_test = x_train / 255.0, x_test / 255.0
-
-model = tf.keras.models.Sequential([
-    tf.keras.layers.Flatten(input_shape=(28, 28)),
-    tf.keras.layers.Dense(128, activation='relu'),
-    tf.keras.layers.Dropout(0.2),
-    tf.keras.layers.Dense(10, activation='softmax')
-])
-
-model.compile(optimizer='adam',
-              loss='sparse_categorical_crossentropy',
-              metrics=['accuracy'])
-
-model.fit(x_train, y_train, epochs=5)
-model.evaluate(x_test, y_test)
\ No newline at end of file