介绍如何安装和配置OpenSSH。
介绍常见操作对文件和目录时间戳的影响。
介绍如何在宿主机中使用虚拟机的VPN连接。
介绍指数加权移动均值的计算方法，并提供SQL和R语言实现。
介绍如何用R语言实现SQL的递归查询。
介绍关于产品待办事项的一些基本知识
介绍关于产品路线图的一些基本知识。
介绍关于产品愿景和产品战略的一些基本知识。
介绍关系数据库物理模型的设计步骤
介绍关系数据库逻辑模型的设计步骤
介绍关系数据库概念模型的设计步骤。
介绍SQL递归查询的写法，并提供一些例子。
介绍数据库的基本范式，并提供具体的示例。
介绍如何部署Gitea，并对服务数据进行备份和恢复。
介绍如何使用传统机器学习算法实现时间序列多步预测。
列出一些常用的自定义函数。
介绍SQL中ON和WHERE的区别，并提供使用建议。
介绍机器学习中一种有效的特征编码方式。
介绍CSV文件格式的规范，以及如何在常用软件中导入和导出该类文件。
介绍层次分析法的一个案例，并提供R语言实现。
介绍常用的Linux用户管理操作。
介绍熵权法的计算方式，并提供R语言实现。
介绍宽带客户流失预警模型的有用特征。
香港游记。
我喜爱的歌曲及演唱者。
介绍如何对Git仓库进行基本的配置。
黑山头古城游记。
衡山游记。
介绍基于CART的回归树的基本原理。
Explains various correlation coefficients.
Guidance on managing SSH connections.
Guidance on installing and using Openfortivpn.
Explains how to plot ROC and precision-recall curves.
Guidance on how to deploy a personal website.
Explains retinamask, a novel network architecture for instance segmentation.
Tidyverse and pandas alternatives for common data merging and splitting operations.
Tidyverse and pandas alternatives for common data tidying operations.
Tidyverse and pandas alternatives for common data transforming operations.
Tidyverse and pandas alternatives for common data importing operations.
Explains various evaluation metrics for object detection.
Explains retinanet, a novel network architecture for object detection.
Explains various indexing methods for numpy arrays.
Guidance on how connecting R to databases.
Guidance on how to install and set up a miniconda environment, with a special focus on data science.
Guidance on setting up a fresh zotero installation.
A brief introduction to git references.
A brief introduction to git objects.
Explains and compares the usage of escape sequences in various programming languages.
Guidance on setting up a fresh datagrip installation.
A follow-up post on getting to know a database.
Compare the differences among different ways of defining and returning PL/pgSQL function outputs.
Shows how to use the information schema to get useful information of various database objects.
Shows how to create user-defined functions in a PostgreSQL database.
Guidance on setting up a fresh visual studio code installation.
A gentle introduction to multivariate adaptive regression splines.
Explains why the accuracy of predictions provided by a classification can be low, even if it can perfectly estimate the probability of an outcome.
Explains bagged trees and random forest in a nutshell.
Guidance on setting up a fresh PostgreSQL installation.
Guidance on setting up a fresh R installation.
Guidance on setting up a fresh Ubuntu installation.
Shows how to fit and interpret a CART classification tree model.
Shows how to make simulated data for logistic regression.
Explains the CART algorithm for classification problems.
Shows how to fit and interpret a CART regression tree model.
Explains bias-variance decomposition with simulation.
Guidance on using continuous archiving and point-in-time recovery with PostgreSQL.
Guidance on installing R and related software.