cyj5201314的博客

引入tensoflow，安装的v2版本但要使用v1的会话import tensorflow.compat.v1 as tfimport numpy as npimport matplotlib.pyplot as plttf.disable_v2_behavior()# numpy生成200个随机点x_data = np.linspace(-0.5,0.5,200)[:,np.newaxis]noise = np.random.normal(0,0.02,x_data.shape)y_.

构建网络构建卷积神经网络，包括4对卷积层和池化层，输出层用sigmoid激活(二分类)，并且对from keras import layersfrom keras import modelsmodel = models.Sequential()model.add(layers.Conv2D(32,(3,3), activation="relu", input_shape=(150,150,3)))model.add(layers.MaxPooling2D((2,2)))model.add(l

京东商品爬虫从https://list.jd.com/list.html?cat=670%2C671%2C673&page=1&s=57&click=0站点进行商品图片爬虫分别爬取手机，pad，笔记本和台式机商品图片各1万张#爬虫代码import reimport requestsfrom multiprocessing.pool import Poolfrom lxml import etreeimport time#爬取每页商品图片urldef crawl(

import osos.environ['TF_CPP_MIN_LOG_LEVEL']='2'import numpy as npfrom keras.datasets import imdbfrom keras import modelsfrom (train_data, train_lables), (test_data, test_lables) = imdb.load_data(num_words=10000)def vectorize_sequences(sequences,

from sklearn.neural_network import MLPClassifier#初始化输入矩阵X = [[0., 0.], [1., 1.]]#初始化目标值y = [0, 1]#实例化一个人工神经网络分类器并传入数据训练clf = MLPClassifier(solver='sgd', alpha=1e-5, activation='logistic',hidde...