UCB CS189: Introduction to Machine Learning - CS自学指南 #185
Replies: 17 comments 26 replies
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好像2022年春季的课程不再开源autograder和notes了,所以有没有哪位大佬能够提供notes呀 |
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找到一个2023 Spring 的 该课程,https://people.eecs.berkeley.edu/~jrs/189/,游客可以访问屏幕录制,好像比油管上的视频更加清晰 |
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spring23的视频:https://www.youtube.com/playlist?list=PLppfe3aWPcD4fthieedXTrE3kQz8rvtJt (偷偷问这是能上传油管的吗🤷 |
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有无大佬有之前的public 的gradescope的激活码啊?最新的2023AU的是E73744,但是有due date,due date之后好像就锁了 |
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sp和fa的版本在内容上有挺大的不同,fa的版本偏理论,难度也较大,具体区别可以参考这个贴子: https://www.reddit.com/r/berkeley/comments/1b67zhw/thoughts_on_fall_cs_189_compared_to_spring_189/ 不过我注意到fa版本的作业似乎没有完全开源,官网中只给出了部分作业的文件,而且也没有答案,如果有同学知道在哪里可以找到这些文件可以分享一下~ |
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好像kaggle不能late submit了 |
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大佬们,求182的 |
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最新的课程视频 2024 Fall https://berkeley-haas.hosted.panopto.com/Panopto/Pages/Sessions/List.aspx#folderID=%22380bd203-98f7-4a83-946e-b1d401302c37%22 |
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看了一下这些课在理论方面还是相对较弱,因为这领域技术迭代比较快,而且学习人员背景复杂,这些教学思路倒也可以。 |
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在学24fall,课程网站突然就变成23fall的了,请问有人存了24fall的homework,discussion吗 |
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今年25fall的课程改了不少,很多传统的内容都没讲,加入了不少深度学习的内容。 |
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我能搞到recording,要一起学吗
…---- 回复的原邮件 ----
发件人 Junqi ***@***.***> 日期 2025年09月05日 18:34 收件人 ***@***.***> 抄送至 David ***@***.***>***@***.***> 主题 Re: [PKUFlyingPig/cs-self-learning] UCB CS189: Introduction to Machine Learning - CS自学指南 (Discussion #185)
似乎今年的课程改革了,老师和slide都很新,有任何25fall的课程资源吗?想试着听听看
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1062109984,建了个群,可以一起
…---- 回复的原邮件 ----
发件人 Junqi ***@***.***> 日期 2025年09月05日 18:34 收件人 ***@***.***> 抄送至 David ***@***.***>***@***.***> 主题 Re: [PKUFlyingPig/cs-self-learning] UCB CS189: Introduction to Machine Learning - CS自学指南 (Discussion #185)
似乎今年的课程改革了,老师和slide都很新,有任何25fall的课程资源吗?想试着听听看
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qq群,the group number of QQ,an app of china
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发件人 ***@***.***> 日期 2025年09月13日 15:36 收件人 ***@***.***> 抄送至 David ***@***.***>***@***.***> 主题 Re: [PKUFlyingPig/cs-self-learning] UCB CS189: Introduction to Machine Learning - CS自学指南 (Discussion #185)
我怎样才能加入这个小组?
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进群直接加就行
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发件人 ***@***.***> 日期 2025年09月13日 17:54 收件人 ***@***.***> 抄送至 David ***@***.***>***@***.***> 主题 Re: [PKUFlyingPig/cs-self-learning] UCB CS189: Introduction to Machine Learning - CS自学指南 (Discussion #185)
还有其他方式观看视频吗?我也想进群。你们有不和谐吗?
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https://github.com/vixitor/berkeleycs189 sp25我在伯克利上过这门课这是当时的笔记可以参考一下,个人感觉这门课难度不是特别大,春季学期来讲,700人的考试最后考了20名喜提A+,这门课最主要的作用对我来说是了解了很多机器学习的概念,但是和现在的ai研究差别还是很大的,如果能力够的话可以直接上神经网络的课,这个课很多都是传统机器学习,神经网络只涉及一点点,然后数学线代概率期望之类的东西比较多 |
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我写的 Spring 2024 版本的所有资料,包括 Discussions, Homework 和 Exams 都在 2025 以及之前的 spring 学期的 CS189 都是 Jonathan Shewchuk 教授讲的,内容以及作业都差不多,偏向传统的 Machine Learning 带一部分 Deep Learning 的内容,Fall2025 的版本改为更加贴近 Deep Learning 的形式,基本不涉及传统 Machine Learning ,数学推导也少了很多,如果有想要打下扎实的 Machine Learning 基础的同学建议学 spring22-25 的版本 |
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UCB CS189: Introduction to Machine Learning - CS自学指南
CS自学指南
https://csdiy.wiki/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/CS189/
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