CS231n: CNN for Visual Recognition
课程简介
- 所属大学：Stanford
- 先修要求：机器学习基础
- 编程语言：Python
- 课程难度：🌟🌟🌟🌟
- 预计学时：80 小时
Stanford 的 CV 入门课，由计算机领域的巨佬李飞飞院士领衔教授（CV 领域划时代的著名数据集 ImageNet 的研究团队），但其内容相对基础且友好，如果上过 CS230 的话可以直接上手 Project 作为练习。
课程资源
- 课程网站：http://cs231n.stanford.edu/
- 课程视频：https://www.bilibili.com/video/BV1nJ411z7fe
- 课程教材：无
- 课程作业：http://cs231n.stanford.edu/schedule.html，3个编程作业
Last update: April 3, 2022
CS231n: CNN for Visual Recognition
Course Introduction
- Affiliated Universities：Stanford
- Prerequisites: Foundations of Machine Learning
- Programming Languages：Python
- Course Difficulty：🌟🌟🌟🌟
- Estimated hours: 80 hours
Stanford's CV introductory class, led by the giant of the computer field, Fei-Fei Li (the research team of the epoch-making famous dataset ImageNet in CV field), but its content is relatively basic and friendly, if you have taken CS230, you can directly start the Project as practice.
Course Resources
- Course Website：http://cs231n.stanford.edu/
- Course Video：https://www.bilibili.com/video/BV1nJ411z7fe
- Course Materials: None
- Coursework：http://cs231n.stanford.edu/schedule.html，3 Programming Assignments
Last update: June 29, 2023