Phase 00: Setup & Tooling

关键字和协作

每个实验,每一个模型,每一个课程都会被追踪.

Type: Learn

Languages: --

Prerequisites: Phase 0, Lesson 01

Time: ~30 minutes

学习目标

配置 git 身份,并使用每天的加,提交和推工作流程
建立和合并分支,进行孤立的实验,而不会打破主体
写一个.gitignore排除模型检查点和大型二元文件
通过导航提交历史git log了解项目发展

问题

你即将在20个阶段写成数百个代码文件. 如果没有版本控制,你会失去工作,打破无法撤销的东西,

这一课涵盖了你需要什么,而不是更多.

概念

sequenceDiagram
    participant WD as Working Directory
    participant SA as Staging Area
    participant LR as Local Repo
    participant R as Remote (GitHub)
    WD->>SA: git add
    SA->>LR: git commit
    LR->>R: git push
    R->>LR: git fetch
    LR->>WD: git pull

记住三个事情:

经常保存 (git commit)
按到远程 (git push)
实验部门 (git checkout -b experiment)

建立它

步骤1:配置 git

bashgit config --global user.name "Your Name"
git config --global user.email "you@example.com"

步骤2:日常工作流程

bashgit status
git add file.py
git commit -m "Add perceptron implementation"
git push origin main

步骤3:为实验分支

bashgit checkout -b experiment/new-optimizer

# ... make changes, commit ...

git checkout main
git merge experiment/new-optimizer

步骤4:与本课程合作

只有维护者才能访问写作. 首先在 GitHub 上 (叉按,右上)origin您的本文:

bashgit clone https://github.com/YOUR-USERNAME/ai-engineering-from-scratch.git
cd ai-engineering-from-scratch

git checkout -b my-progress
# work through lessons, commit your code
git push origin my-progress

用它

为了完成这个课程,你需要这些命令:

Command	When
`git clone`	Get the course repo
`git add` + `git commit`	Save your work
`git push`	Back it up to GitHub
`git checkout -b`	Try something without breaking main
`git log --oneline`	See what you've done

这就是,你不需要反,桃选,或子模块.

运动

叉这个 repo,克隆你的叉子,创建一个叫做my-progress写一个文件,提交它,推它
创建一个.gitignore没有模拟检查站文件 (.pt现在.pth现在.safetensors)
查看这个回复的提交历史git log --oneline阅读如何增加教训

关键词

Term	What people say	What it actually means
Commit	"Saving"	A snapshot of your entire project at a point in time
Branch	"A copy"	A pointer to a commit that moves forward as you work
Merge	"Combining code"	Taking changes from one branch and applying them to another
Remote	"The cloud"	A copy of your repo hosted somewhere else (GitHub, GitLab)

This free lesson is part of the AI Engineering from Scratch curriculum. Read the full explanation, run the lesson code, and verify the result in the interactive reader or from the repository source.

Browse the complete course catalog or open this lesson on GitHub.