我的ML学习之旅(Coursera)
亲测在Coursera学起来很爽的顺序：
Machine Learning Specialization (MLS) ---> Deep Learning Specialization (DLS)
这篇只分享我在Coursera上的学习。这两门课程都需付费，虽说有7天free trial，但是7天其实学不完的哈哈哈哈哈哈哈。
MLS非常非常适合入门。DLS适合回顾。
从课程制作的成熟度可以看出来，DLS比MLS更早发布，不如前者易懂，所以DLS不适合完全没接触过的朋友。两者有部分内容重合。
学这个最重要的是：别担心！最喜欢Andrew Ng的那句话，如听仙乐：If you don't know the details of xxx, don't worry about it. 这句话贯穿了他的两个Specializations。
前几天开始补ML必要的数学知识，于是点开了Mathematics for Machine Learning and Data Science Specialization。没想到在导学视频里，Andrew自己也意识到了：
When it comes to math, I sometimes said don't worry about it. And I actually stand by that. When you're learning machine learning for the first time to get it to work, sometimes you don't need to worry about the intricacies of exactly how the math works. But as Luis was saying, to get to that next level of expertise, when you can then start to gain that deeper understanding of that math as well. You can then learn a better, deeper mastery of the algorithms that you're using and building.
最后，强烈建议同时看3b1b（油管的3blue1brown博主的视频）的essence of linear algebra和essence of calculus系列，真的开眼了。最好的教学！我爱！在Mathematics for Machine Learning and Data Science Specialization的补充资料里也提到了这位教学大牛。
感恩♥️