摘要: Spiking Neural Network Algorithm Spiking Neural Networks (SNNs) are a type of neural network that aim to more closely mimic the behavior of biological 阅读全文
posted @ 2024-07-08 21:09 热爱工作的宁致桑 阅读(18) 评论(0) 推荐(0) 编辑
摘要: The pd.concat() function in pandas is a powerful tool for concatenating or "stacking" together objects along a particular axis. This function can take 阅读全文
posted @ 2024-02-14 22:45 热爱工作的宁致桑 阅读(7) 评论(0) 推荐(0) 编辑
摘要: The chi-square distribution is a continuous probability distribution that is widely used in statistical inference, particularly in the context of hypo 阅读全文
posted @ 2024-02-14 17:13 热爱工作的宁致桑 阅读(12) 评论(0) 推荐(0) 编辑
摘要: The number of ways to choose \( x \) items from \( n \) items is given by the binomial coefficient, which is calculated using the combination formula: 阅读全文
posted @ 2024-02-13 10:41 热爱工作的宁致桑 阅读(7) 评论(0) 推荐(0) 编辑
摘要: 收集好的txt数据要先过滤一下,删掉无效信息。然后再按下面步骤处理 class DataPreprocessor(): '''def __init__(self, vocab_file, longest_sentence): self.tok = BertTokenizer(vocab_file) 阅读全文
posted @ 2023-09-20 20:22 热爱工作的宁致桑 阅读(64) 评论(0) 推荐(0) 编辑
摘要: # 将所有txt文件拷贝至alltxt这个文件夹 import os import shutil # Create new folder if it doesn't exist if not os.path.exists("alltxt"): os.makedirs("alltxt") # Loop 阅读全文
posted @ 2023-09-20 20:14 热爱工作的宁致桑 阅读(9) 评论(0) 推荐(0) 编辑
摘要: import requests from lxml import etree def create_request(page): if page == 1: url = 'http://www.zhb.org.cn/hbzx/news_2' else: url = 'http://www.zhb.o 阅读全文
posted @ 2023-09-18 20:52 热爱工作的宁致桑 阅读(14) 评论(0) 推荐(0) 编辑
摘要: import urllib.request from lxml import etree def create_request(page): if page == 1: url = 'http://www.chinaeol.net/hjxw/gnxw' else: url = 'http://www 阅读全文
posted @ 2023-09-18 20:07 热爱工作的宁致桑 阅读(6) 评论(0) 推荐(0) 编辑
摘要: from selenium import webdriver from selenium.webdriver.common.keys import Keys from selenium.webdriver.common.by import By from selenium.webdriver.chr 阅读全文
posted @ 2023-09-18 19:19 热爱工作的宁致桑 阅读(6) 评论(0) 推荐(0) 编辑
摘要: import pandas as pd import numpy as np data = pd.read_excel("2005-2023年国泰安数据库上市公司向银行借款表.xlsx") data = data.drop(index=[0,1]) data['rate_up'] = None da 阅读全文
posted @ 2023-09-13 19:25 热爱工作的宁致桑 阅读(12) 评论(0) 推荐(0) 编辑