coursera: Machine Learning - CS%E8%87%AA%E5%AD%A6%E6%8C%87%E5%8D%97 #154
giscus[bot]
bot
Replies: 10 comments 20 replies
-
|
可以用异步图书的零基础向机械学习 作为入门 其他的我还在探索 |
Beta Was this translation helpful? Give feedback.
-
|
请问coursera的实验除去optional lab，剩下的实验是不是很少啊 |
Beta Was this translation helpful? Give feedback.
-
|
推荐 Coursera 国立台湾大学的“機器學習基石”和“機器學習技法”两节课程。感觉理论更多一些 |
Beta Was this translation helpful? Give feedback.
-
|
我又回来了。这两门课很好，但是不推荐作为机器学习入门。我还是觉得先看 UMich 的课（csdiy 里有）比较好。UMich 可以让你熟练运用 PyTorch，而且通过丰富的例子，让你对这方面有很好的感性认知。 不足之处，就是 UMich 只教深度学习，对于传统机器学习的部分少了很多。但是个人认为，毕竟深度学习很强大+很fancy，容易提起初学者的兴趣，因此可以适合作为入门。 |
Beta Was this translation helpful? Give feedback.
-
|
请问Umich是在csdiy的哪一部分里介绍呢？我找了一下没有找到 |
Beta Was this translation helpful? Give feedback.
-
|
深度学习里边的UMich EECS498 |
Beta Was this translation helpful? Give feedback.
-
|
完全没有学过ml，可以先学UMich的课再去学传统机器学习吗？ |
Beta Was this translation helpful? Give feedback.
-
|
国内的可以去看看浙大的胡浩基老师讲的。 |
Beta Was this translation helpful? Give feedback.
-
|
这个交作业竟然要绑定银行卡🤔 |
Beta Was this translation helpful? Give feedback.
-
|
已经邮件私信，十分感谢！！！ |
Beta Was this translation helpful? Give feedback.
-
|
我淘宝上买了一个plus包括这节课～ |
Beta Was this translation helpful? Give feedback.
-
|
同求一个账号~ |
Beta Was this translation helpful? Give feedback.
-
|
看看可不可以在 Coursera 上申请助学金啥的？我之前上 Algorithm Specification 的时候，就去申请了助学金。 |
Beta Was this translation helpful? Give feedback.
-
|
可以申请助学金的，基本都能给过 |
Beta Was this translation helpful? Give feedback.
-
|
学完感觉很空，如果要自己实现机器学习算法还是不行，之后有没有什么好的学习路径呢，感觉这个最多属于科普 |
Beta Was this translation helpful? Give feedback.
-
|
理论的话可以学台湾大学林轩田的《机器学习基石》和《机器学习技法》。我看完了，但是这门课其实不应该一开始上，因为数学太多而感性认知太少，而且虽然留了作业，但是不给代码框架，也不教怎么使用 torch, tf 等，写起来一头雾水。适合进阶看。 如果想看看深度学习+计算机视觉+顺便熟练运用 PyTorch 的话，可以看看 UMich EECS 498-007/598/005。有好几个作业，从最开始的熟悉 PyTorch，到最后实现 variational auto-encoder 和 GAN。我目前还在看，挺有意思的。 |
Beta Was this translation helpful? Give feedback.
-
|
一个半月后回复：Umich 的课确实挺好的，目前还在看，csdiy 里应该是有的。 |
Beta Was this translation helpful? Give feedback.
-
|
你好，请问看完吴恩达的机器学习课程了解到基本的概念之后，是把他布置的lab写一下，还是去看cs231n或者UMich EECS498 |
Beta Was this translation helpful? Give feedback.
-
|
我觉得lab才是精髓，尤其是对python不熟悉的人也是对python很好的联系。对于有数学基础的人来说课很快就能看完（基本上一天一个course） |
Beta Was this translation helpful? Give feedback.
-
|
其实不熟练使用python一开始也可以上手 |
Beta Was this translation helpful? Give feedback.
-
|
跟写了代码实现，纯py代码，有绘制图像以及文档说明，持续更新 |
Beta Was this translation helpful? Give feedback.
-
|
请问佬，也是跟着Coursera:Machine Learning的旁听来跟写了代码实现的吗 |
Beta Was this translation helpful? Give feedback.
-
|
是的，但是只是第一部分 |
Beta Was this translation helpful? Give feedback.
-
|
暑假继续跟 |
Beta Was this translation helpful? Give feedback.
-
|
【(超爽中英!) 2024公认最好的【吴恩达机器学习】教程！附课件代码 Machine Learning Specialization】 https://www.bilibili.com/video/BV1Bq421A74G/?share_source=copy_web&vd_source=343bef2897116ac8457328069e8fc81a |
Beta Was this translation helpful? Give feedback.
-
|
有学过的uu讲一下吗，这个是不是过于简单？ |
Beta Was this translation helpful? Give feedback.
Uh oh!
There was an error while loading. Please reload this page.
-
coursera: Machine Learning - CS%E8%87%AA%E5%AD%A6%E6%8C%87%E5%8D%97
CS自学指南
https://csdiy.wiki/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/ML/
Beta Was this translation helpful? Give feedback.
All reactions