Open Source Computer Vision Library（OpenCV）是一个跨平台的计算机视觉库，可用于开发实时的图像处理、计算机视觉以及模式识别程序。OpenCV 用 C++ 语言编写，但本次实战项目使用的是
python-opencv库实现的，主要是为了初步了解人脸识别的步骤和算法后面的原理。源代码保存在 Github 仓库 中。以下为我在实战练习过程中所做的笔记，可供参考。
偶然刷到一篇名为《一半人写不出冒泡排序，你的同龄人都躺下了》的文章，其中提到轮子哥毕业去参加面试的时候，第一轮笔试考察冒泡排序，结果现场的一半学生都没写出来。冒泡排序（Bubble Sort），是一种最基础的、最简单直观的交换排序，之所以叫做冒泡排序，是因为越小的元素会经由交换慢慢“浮”到数列的顶端（升序或降序排列），就如同碳酸饮料中二氧化碳的气泡最终会上浮到顶端一样。以下为我总结的实现思想和代码，可供参考。
双色球是最常见的一种彩票。双色球投注区分为红球号码区和蓝球号码区，红球号码范围为01～33，蓝球号码范围为01～16。双色球每期从33个红球中开出6个号码，从16个蓝球中开出1个号码作为中奖号码，双色球玩法即是竞猜开奖号码的6个红球号码和1个蓝球号码，顺序不限。以下为我的代码设计和实现，可供参考。
Java 语言是 SUN (Stanford University Network) 公司于1995年推出的一门高级编程语言，舍弃了 C 语言中容易引起错误的指针（以引用取代）、运算符重载（operator overloading）、多重继承 （以接口取代）等特性，增加了垃圾回收器等功能，具有面向对象、健壮性、跨平台性等特性。我选择的 Java课程为尚学堂 Java 零基础入门教程，但由于我个人不是零基础入门，所以这篇笔记不含编程入门和语言概述，仅包含 Java 基础编程知识的总结。
Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don’t have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand. This course provided by IBM shares a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and properly manipulated to address the question at hand. The following are the notes I took during this course.
IntelliJ IDEA 被公认为是最好的 Java 开发工具之一，尤其在智能代码助手、代码自动提示、重构、J2EE 支持、Ant、JUnit、CVS 整合、代码审查、创新的GUI 设计等方面的功能可以说是超常的。相较于 Eclipse 而言，IDEA 增加了强大的整合能力、好用的快捷键和代码模板以及精准搜索，一些新的特性非常有必要学习熟悉。我目前使用的是 IDEA Ultimate 2021.2 版本，本篇笔记也是对最新版 IDEA 项目的创建、模板的使用、断点调试、数据库的关联、插件的下载、Maven及版本控制工具的配置等内容的一些总结。
In this course provided by IBM, I learned about Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio, what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Skills Network Labs, I can now run simple code in Python, R or Scala. The following are the notes I took during this course.
Jupyter Notebook 是基于浏览器网页的用于交互计算的应用程序，支持 Python、R、Julia 和 Scala 等多种语言，在数据科学相关领域有着非常大的用途。JupyterLab 是基于 web 的集成开发环境，包含了 Jupyter Notebook 所有功能的同时还支持操作终端、编辑 markdown 文本、打开交互模式、查看 csv 文件及图片等功能，最近在学习的 IBM 数据科学专项课程也都是基于 Jupyter Lab 的，在阿里云主机上部署 Jupyter 环境也能使研究和学习更加方便。以下为我总结的一些操作步骤和流程，可供参考。
阿里云基础认证（ACA - Alibaba Cloud Certified Associate）是面向使用阿里云基础产品的专业技术认证，主要涉及阿里云的计算、存储、网络、安全类的核心产品。 阿里云云计算助理工程师的培训和认证的过程能够提升个人对云计算产品技术的理解，可以对这些产品进行基本的日常管理，也可以基于这些产品进行应用的部署，从而证明个人在云计算领域的专业能力，获得更多就业机会。以下为我在学习过程中所做的笔记，可供参考。
The art of uncovering the insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year. Since then, people working in data science have carved out a unique and distinct field for the work they do. This field is data science. This course provided by IBM gives me a chance to get an overview of what data science is today. The following are the notes I took during this course.
最近购买了阿里云学生机（轻量应用服务器，单核2G内存），预装载 CentOS 7.6。官方推荐 Putty 连接，我使用的 SSH 软件为 Xshell，用 Xftp 传输文件。第一次接触云服务器，在云主机上搭建 LAMP 环境并部署 Wordpress 博客应用，以下为我总结的一些操作步骤和流程，仅供测试参考。
In this course provided by IBM, I will assume the role of an Associate Data Analyst who has recently joined the organization and be presented with a business challenge that requires data analysis to be performed on real-world datasets. The capstone project will culminate with a presentation of your data analysis report, with an executive summary for the various stakeholders in the organization. I believe this project is a great opportunity to showcase Data Analytics skills, and demonstrate proficiency to potential employers. The following are the notes I took during this course.
本期训练营是阿里云开发者社区Java训练营的第3期，主要基于最流行的Java Spring Cloud, 结合阿里巴巴淘宝微服务案例，实战模拟淘宝Order微服务，实战演练微服务开发，扩展学习Spring Cloud Alibaba新框架，本篇日志主要记录5天直播Spring cloud微服务开发课中的一些知识点，附实战代码。
This Data Analysis with Python course provided by IBM is designed to teach future data analysts how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data through a number of lecture, lab, and assignments using Python libraries. The following are the notes I took during this course.
Linus Torvalds，一个任何极客都不会陌生的名字，Linux之父、Git之父，大神在计算机领域的影响力可以说是划时代的。那么在这些传奇的背后蕴藏着怎样的思想呢？下面这个Linus2016年时在TED上接受的一次访谈或许能让我们对Linux背后的思想略窥一二。
One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way. Learning how to leverage a software tool to visualize data will helps one understand the data better, and make more effective decisions. The main goal of this Data Visualization with Python course provided by IBM is to use various techniques and several data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium for presenting data visually. The following are the notes I took during this course.
This Python Project mini-course provided by IBM is intended to demonstrate basic Python skills by performing specific tasks such as extracting data, web scraping, visualizing data, and creating a dashboard. The following are the notes I took during this course.