批量數據處理，next_batch()

# 隨機取batch_size個訓練樣本
import numpy as np
#train_data訓練集特征，train_target訓練集對應的標簽，batch_size
def next_batch(train_data, train_target, batch_size):
#打亂數據集
index = [ i for i in range(0,len(train_target)) ]
np.random.shuffle(index);
#建立batch_data與batch_target的空列表
batch_data = [];
batch_target = [];
#向空列表加入訓練集及標簽
for i in range(0,batch_size):
batch_data.append(train_data[index[i]]);
batch_target.append(train_target[index[i]])
return batch_data, batch_target #返回
————————————————
版權聲明：本文為CSDN博主「黃鑫huangxin」的原創文章，遵循 CC 4.0 BY-SA 版權協議，轉載請附上原文出處鏈接及本聲明。
原文鏈接：https://blog.csdn.net/qq_33373858/article/details/83012236