Thoughts From Your Humble Curators
Its AWS re:INVENT week - this is the big annual AWS conference. Amazon had several announcements on its AI offerings. So we will take a closer look in this Issue.
In our Blogs Posts section, we have a line-up of many interesting blog posts and paper reviews this issue, including:
- Google Vision AIY Kit,
- Stephen Merity on Understanding the Mixture of Softmaxes (MoS),
- One LEGO at a time: Explaining the Math of How Neural Networks Learn,
- Arthur's Review of Course 3 of deeplearning.ai
We also present our read on the CheXnet paper which alleged beat human radiologists. We are taking a closer look of the results.
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Are MOOC Certificates Important?
Our thought (from Arthur): For the most part, MOOC certificates don't mean too much in real life. It is whether you can actually solve problem matters. So the meaning of MOOC is really there to stimulate you to learn. And certificate serves as a motivation tool.
As for OP's question. I never got the Udacity nanodegree. From what I heard though, I will say the nanodegree will require effort to take 1 to 2 Ng's deeplearning.ai specialization. It's also tougher if you need to take a course in a specified period of time. But the upside is there are human graders that give you feedback.
As for which path to go, I think it solely depends on your finances. Let's push to an extreme: e.g. If you purely think of credential and opportunities, perhaps an actual PhD/Master degree will give you the most, but then the downside is multi-year salary opportunity costs. One tier down would be online ML degree from Georgia tech, but it will still cost you up to $5k. Then there is taking cs231n or cs224d from Stanford online, again that will cost you $4k/class. So that's why you would consider to take MOOC. And as I said which price tag you choose depends on how motivate you are and how much feedbacks you want to get.