cs188 - sp24¶

中文 | English

# Licensing Information: You are free to use or extend these projects for
# educational purposes provided that (1) you do not distribute or publish
# solutions, (2) you retain this notice, and (3) you provide clear
# attribution to UC Berkeley, including a link to http://ai.berkeley.edu.

Introduction¶

This repository contains notes & self-study materials for UCB's CS 188 Spring 2024. In theory, all the materials you need to study this course can be found here and in the external links provided. Projects are from ai.berkeley.edu.

• Notes: The main body consists of the original course notes¹, augmented with my own thoughts and formatting. You can read these notes on my blog. However, for a better viewing experience, Obsidian is recommended². See Usage - Reading.
• Self-study materials: As some of UCB's courses in recent years require CalNet Authentication Service, I have archived materials that I consider necessary for self-study in this repository for easier future learning. Since I am unsure how to apply for reprint permission, if this project negatively impacts the original course and its related projects, please contact me to remove it.

• If you are already familiar with search algorithms, comfortable with ML/DL/RL knowledge, and interested in exploring small project files, you can directly tackle the projects.

• 【20250619 Update】Coincidentally, I took a Statistical Machine Learning course this semester, which has deepened my understanding of concepts I only partially grasped during CS188. I have added corresponding links to the prerequisites (below are some introductions, not directly related to CS188; in retrospect, CS188 feels more like a toy, but it aligns well with the course title).

  • On one hand, from the AI Algorithm Engineer Handbook, which is a more comprehensive and complete Chinese resource.
  • On the other hand, from Data modeling and analysis, which are my notes from studying the school's "Data Modeling and Analysis" course, adjusted as I learned, with the help of Gemini 2.5 processing PPTs. I believe it explains things quite clearly (before taking this course, my probability and statistics skills were close to high school level).
  • Additionally, for some difficult points, I consulted Wang Mutou Learning Science, which is detailed and easy to understand, but unfortunately, the uploader hasn't updated in a long time.

Table of Contents¶

note&project¶

(The order of the table of contents will change with my last modification time; you can refer to the sidebar navigation.)

materials¶

• course_page
  • Course website calendar, for easy self-study planning.
• disc
  • Related discussion questions and their solutions.
• origianl_note
  • Original course notes. Theoretically, the notes above should suffice.
• project
  • original_zip
    • Original project source code.
  • intro_page
    • Retained page files for experiment documentation.
  • solution
    • Reference code (moved to cs188/project/solution/)
    • Direct runnable code removed based on course code license.
• gradecode
  • 4VK322

Usage¶

Download¶

Using Git¶

git clone https://github.com/darstib/cs188.git

Direct Download All¶

Partial Download¶

If you only want the notes, projects, or any other single folder, you can use DownGit. Enter the URL of the desired folder within this git repository.

Reading¶

For a good reading experience from the beginning, you can refer here. If you don't have high expectations, a simpler version is as follows:

1. Get Obsidian.
2. Import Markdown.
3. Click the top-right corner to enter reading view.

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