神经网络_使用tensorflow对mnist手写数字分类

from pathlib import Path
import requests
import pickle 
import gzip
from matplotlib import pyplot as plt
import numpy as np
import tensorflow as tf
from tensorflow.keras import layers
from tensorflow.keras.utils import to_categorical
import pandas as pd 
%matplotlib inline

1. 数据预处理

data_path = Path("data/mnist")
data_path.mkdir(parents=True, exist_ok=True)

#是否从网络下载数据文件
source_data_file_from_net = False

#下载数据
#此网址打开较慢，可以使用 https://tianchi.aliyun.com/dataset/165658 阿里云下载
mnist_url = "http://deeplearning.net/data/mnist/"
mnist_zip_name = "mnist.pkl.gz"

if source_data_file_from_net:
    if not (data_path/mnist_zip_name).exists:
        content = requests.get(mnist_url + mnist_zip_name).content
        (data_path / mnist_zip_name).open('wb').write(content)
        ((x_train, y_train),(x_valid, y_valid), _) = pick.load(f, encoding='latin-1')
    else:    
        with gzip.open((data_path / mnist_zip_name).as_posix(), "rb") as data_file:
            ((x_train, y_train)