Year-end Article Review and New Menu Release¶

1 Introduction¶

Although it is not yet the end of the lunar year, the gradually colder weather and the upcoming year-end review seem to add some correctness to the act of doing a "year-end review".

Our project started at the end of May, and as an important component, the WeChat official account is a place for us to record knowledge related to data science. It can motivate us to learn new knowledge, and it is also convenient to look back on in the future and review what we have learned. If it can also provide value for readers, that would be even better.

Therefore, our choice of articles is always a bit arbitrary, and over time, it may seem a bit messy. Taking this opportunity, we have reorganized the classification of articles and released a new menu. More importantly, we also want to take this opportunity to review the articles we have published and do a "year-end summary".

2 Main Course of Technology¶

The main course of technology focuses on hardcore programming and AI content, and is also the most output part of our content. It is divided into three sub-parts: artificial intelligence, programming essences, and analysis tools.

2.1 Artificial Intelligence¶

The artificial intelligence section focuses on algorithms and applications related to machine learning, AI (Artificial Intelligence), including the following four points:

• Experience sharing
• Deep learning
• Algorithms
• Competitions

In the experience sharing section, we mainly share tricks based on our own experience (troubleshooting experience) and high-quality resources such as "Rules of Machine Learning", "A Recipe for Training Neural Networks", and Kaggle forum during the entire process of applying machine learning modeling.

For us, these experiences are all valuable, cannot be directly looked up, and could only be learned by spending a lot of time and efforts.

The deep learning section mainly introduces the machine learning framework Tensorflow, including how to install it on Apple Silicon Macs, various callbacks, how to customize models, and how to build a model to recognize flower images with biased applications. If you want to learn Tensorflow better, why not check out our deep learning topic?

The algorithm part includes recursion, search, sorting in data structures and algorithms, decision trees in machine learning, multi-task algorithms, and double difference models that can be used in strategies.

The competition section is about the competitions we have participated in or interpretations of open source solutions with high scores. Learning from the experts always yields a lot.

2.2 Programming Essences¶

Programming essences involve the programming languages and related applications we often use, including the following three points:

• Python
• SQL
• Applications

We use Python and SQL the most. In the Python section, we introduce common data structures including dictionaries, lists, and tuples, as well as the useful PySpark package for processing big data.

In the SQL section, we first introduce common data warehouses. Then, we focus on introducing the popular data warehouse SnowFlake and its architecture, permission, and practical guidelines in the usage process. Finally, we introduce the Python package that can parse SQL statements: sqlparse.

The application section includes various fun applications. Technology is not only cool but also practical. We introduce how to use Python to build a Taobao grabbing robot, reserve tennis courts, crawl job information and PDF files, build a forum, and intelligent ordering on 12306. We also introduce A/B testing, which is a very useful analysis methodology in both work and life.

2.3 Analysis Tools¶

Analysis tools introduce the basic infrastructure that are indispensable in the program development process:

• Git
• Containers

Git mainly provides version control and work management functions. We introduce how to use GitHub and common commands. GitHub can also be fun. We introduce some cool features of GitHub, such as GitHub Action and using GitHub to make an online resume.

Docker allows developers to package applications and dependencies into containers, making development easier. We introduce what Docker is and how to run Docker on Windows systems step by step.

3 Technology Desserts¶

So much hardcore knowledge may overwhelm some of our readers. We also provide technology desserts to let everyone relax and have some fun. It focuses on the experience sharing in software and hardware and is divided into four parts: experience sharing, product experience, apps, and iOS.

3.1 Experience Sharing¶

Experience sharing includes our original story and how to write WeChat articles scientifically.

3.2 Product Experience¶

Product experience mainly shares our experience in using hardware, including M1 Mac mini, Apple Watch S5, iPad Pro, and Logitech mouse. We do not carry any goods or have any advertising fees, so this is our most authentic evaluation.

3.3 Apps¶

The Apps section includes some useful software, including the good-looking personal note-taking application Notion, PicGo image bed for uploading images, code generation tool Copilot, code hosting platform GitHub, practical computer software, and Google Analytics for analyzing website traffic.

3.4 iOS¶

We have senior Apple fans in our team, so we introduce some useful tools in the iOS usage process. With these tools, we believe that the user experience can be greatly improved.

4 Conclusion¶

It has been almost half a year since our project Kickoff. Although we do not have many fans, we continue to tirelessly output knowledge related to data science and enjoy doing so.

This "year-end summary" introduces our newly organized new menu, hoping that everyone will have the interest to take a look. We also reviewed the more than 50 articles and videos we released. If 1% of the content is useful to you, then we have achieved our goal.

Finally, thank you for accompanying us, our readers!

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