/ ****************************************************************************** * Created on : 2017-5-30 17:12 * author : 硫酸亚铜 *需要在solution->Run Calculation->Options勾选Data Sampling for Time Statistics *否则会报错 ****************************************

上一篇写了<Entity Farmework领域建模方式 3种编程方式>,现在就Code First 继续学习 1.数据库表的创建 新建一个MVC的项目,在引用右击管理NuGet程序包,点击浏览搜索EF安装,我这里主要是EF6.0 以上的学习 所以都安装6.0 以上的版本 接下来在Model文件夹下面创建一个Customer类 public class Customer { public int ID { get; set; } public string Name { get; set; }

一. 简介 1. 优先级:Fluent API > data annotations > default conventions. 2. 所有的Fluent API配置都要在 OnModelCreating这个重写方法中进行 3. 常见的配置:  ① 获取表对应的配置根: var stu =modelBuilder.Entity<XXX>();  ② 设置主键:HasKey<string>(s => s.studentKey);  ③ 获取属性:stu.Prope

Fluent API in Code-First: We have seen different DataAnnotations attributes in the previous sections to override default Code-First Conventions. Here, we will learn about Fluent API. Fluent API is another way to configure your domain classes. Fluent

原文地址:https://www.infoq.com/articles/reactor-by-example Key takeaways Reactor is a reactive streams library targeting Java 8 and providing an Rx-conforming API It uses the same approach and philosophy as RxJava despite some API differences It is a 4th

视频见https://developers.google.com/google-test-automation-conference/2015/stream,文档见https://developers.google.com/google-test-automation-conference/2015/presentations另Google developer应该已经解禁,无需FQ,大家可以测试下.不过视频还是在youtube上,https://www.youtube.com/playlist?

Common Pitfalls In Machine Learning Projects In a recent presentation, Ben Hamner described the common pitfalls in machine learning projects he and his colleagues have observed during competitions on Kaggle. The talk was titled "Machine Learning Grem

Curse of Dimensionality Curse of Dimensionality refers to non-intuitive properties of data observed when working in high-dimensional space *, specifically related to usability and interpretation of distances and volumes. This is one of my favourite t

Large Scale Visual Recognition Challenge 2015 (ILSVRC2015) Legend: Yellow background = winner in this task according to this metric; authors are willing to reveal the method White background = authors are willing to reveal the method Grey background

EntityFramework Core 学习系列(一)Creating Model Getting Started 使用Command Line 来添加 Package  dotnet add package Microsoft.EntityFrameworkCore.SqlServer 使用 -v 可以指定相应包的版本号. 使用dotnet ef 命令  需要在.csproj 文件中包含下面引用 <ItemGroup> <DotNetCliToolReference Include=

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这篇论文提出了一种新的局部描述子学习方法,有一些点值得学习,记录下来以供参考.文章中涉及了一些3D reconstruction.structure from 的知识,不是很了解,所以理解可能有偏颇. 一.介绍 基于网络学习的局部描述子在patch-based benchmark取得了很好的结果,但是在最近image-based 3D reconstruction的benchmarks上面没有得到泛化性能的验证.所以作者提出一种描述子学习方法,可以受益于数据生成,数据采样,以及损失函数.这三点一

How can you add extra hardware UARTs to a 32bit TMS470 ARM7-based microcontroller at zero cost? Solution: Designers can use the high-end timer (HET) peripheral found on all Texas Instruments ARM7-based, 32-bit TMS470 microcontrollers to implement add

From : http://www.oschina.net/news/53070/haproxy-1-5-0 经过 4 年的不懈努力,HAProxy 1.5.0 终于发布了! 相对于 1.4 版本来说,1.5 版本包括了许多新特性和性能改进: 支持 SNI/NPN/ALPN 和 OCSP stapling 的原生 SSL: 支持 IPv6 和 UNIX sockets: full HTTP keep-alive for better support of NTLM and improved ef

一.概述 HBase官方提供了基于Mapreduce的批量数据导入工具:Bulk load和ImportTsv.关于Bulk load大家可以看下我另一篇博文. 通常HBase用户会使用HBase API导数,但是如果一次性导入大批量数据,可能占用大量Regionserver资源,影响存储在该Regionserver上其他表的查询,本文将会从源码上解析ImportTsv数据导入工具,探究如何高效导入数据到HBase. 二.ImportTsv介绍 ImportTsv是Hbase提供的一个命令行工具

Network Time Protocol互联网时间协议 NTP is intended to synchronize all participating computers to within a few milliseconds of Coordinated Universal Time (UTC).[1]:3 It uses a modified version of Marzullo's algorithm to select accurate time servers and is d

一,简介 这个模块包含一系列的常用图像处理算法. 二,分析 此模块包含的文件如下图: 其导出算法包括如下: /*********************** Background statistics accumulation *****************************/ /* Adds image to accumulator */ CVAPI(void) cvAcc( const CvArr* image, CvArr* sum, const CvArr* mask CV_D

How to handle Imbalanced Classification Problems in machine learning? from:https://www.analyticsvidhya.com/blog/2017/03/imbalanced-classification-problem/ Introduction If you have spent some time in machine learning and data science, you would have d

zh.wikipedia.org/wiki/Bagging算法 Bagging算法 (英语:Bootstrap aggregating,引导聚集算法),又称装袋算法,是机器学习领域的一种团体学习算法.最初由Leo Breiman于1994年提出.Bagging算法可与其他分类.回归算法结合,提高其准确率.稳定性的同时,通过降低结果的方差,避免过拟合的发生. 给定一个大小为的训练集,Bagging算法从中均匀.有放回地(即使用自助抽样法)选出个大小为的子集,作为新的训练集.在这个训练集上使用分类.

post post Table of Contents 1. Post-processing 1.1. Reverse flow 1.1.1. reasons 1.1.2. solutions 1.2. variable definitions– ch34, field function definitions, user guide, fluent 1.3. Residuals 1.3.1. access to the residual values for each cell in my f