天上掉下两毛钱

import tensorflow as tfimport numpy as npx_data =np.random.rand(100).astype(np.float32)y_data=x_data*0.1 +0.3Weights=tf.Variable(tf.random_uniform([1],-1.0,1.0))biases=tf.Variable(tf.zeros([1])...

 添加了4个卷积，每个卷积后边跟了池化层，最后加了3个全连接层。def model(input_tensor, train, regularizer): with tf.variable_scope('layer1-conv1'): # 定义一个作用域：layer1-conv1，在该作用域下面可以定义相同名称的变量（用于变量） conv1_w...

import tensorflow as tf# 声明两个变量v1 = tf.Variable(tf.random_normal([1, 2]), name="v1")v2 = tf.Variable(tf.random_normal([2, 3]), name="v2")init_op = tf.global_variables_initializer() # 初始化全部变量sav...

import tensorflow as tfimport numpy as npimport pandas as pd#数据预处理def read_data(): data=pd.read_csv('train.csv') #pandas 读取 data=data.fillna(0) #NAN 填入0 datax=data[['Sex', 'Ag...

import pandas as pddef make_data(): col_names = ["ID","K1K2驱动信号","电子锁驱动信号","急停信号","门禁信号","THDV-M","THDI-M","label"] data = pd.read_csv("data_train.csv",nam

>> x = np.arange(3)>> xarray([0, 1, 2])>> x.shape(3,)>> x[:, np.newaxis]array([[0], [1], [2]])>> x[:, None]array([[0], [1], [2]])&...

import tensorflow as tfimport numpy as npdef add_layer(inputs, in_size, out_size, activation_function=None): Weights = tf.Variable(tf.random_normal([in_size, out_size])) biases = tf.Variable...

from keras.applications.inception_v3 import InceptionV3from keras.models import Modelfrom keras.layers import Dense, GlobalAveragePooling2D,Flattenfrom skimage import io, transformimport globimp...