Wow, this is really a great resource. I wish it had been available a few years back when I took the free online version of CS231n. The hardest part (for me, anyway) was the long-forgotten Calculus needed for backprop. Especially as applied to matrices. I struggled at the time to find accessible explanations of many of the matrix operations, and you seem to have it all laid out here. Thank you.
Adding my own anecdote, there seems to be some kind of problem with high I/O loads on High Sierra.
One of my projects involves indexing thousands of URLs. During development I use a large (80GB+) local cache of a few million files. Running the cache code (~100 lines of simple Golang) totally brings my iMac (3.8GHz Core i5, 24GB) to its knees. CPU shows as mostly idle & memory pressure is low, yet the machine can't redraw windows properly after about 5GB of I/O to local SSD.
Completely frustrating. I moved the code over to an older (2010!) Mac running Ubuntu and it handles it without breaking a sweat.
Paranoid patient question: when one goes for an MRI, is there any kind of scan for foreign metal objects? I'm sure they ask if you have any devices implanted, but do they actually check for the unexpected? What would happen if you had one of these little bristles and you didn't know it?
I'm not aware of any such scan, and I'd feel a lot safer if there were such a tool. I simply can't be sure if I have any embedded metal fragments, and do not want to discover this by having any such pieces rip through my body.
My father has worked with metal his whole life. If just a tiny sliver of metal shaving landed in his eye and worked it's way around to the back, an MRI would tear it straight through the eye ball.
I think the concern is more that a sentience that is many orders of magnitude more intelligent than humans simply won't care about us. How do you feel about ants?
I like to build something that I've programmed before in another language. Maybe this seems redundant. But if you have the problem fresh in your mind, it leads to asking the kinds of (Googleable) questions that get you very quickly to a base-level understanding of the new language. It also sheds light on the areas where the language is better/worse at specific things than the lang you are used to working with.
I used to use this method, but I've started to back away from it, because I often find that it encourages my own Blub programmer nature. Re-implementing an old project immediately shows me the ways in which the new language is worse, but often obscures the benefits.
As a personally embarrassing example, I once returned to Python after three years of heavy Scheme usage. I spent a week porting an almost trivial application and it felt like Python was fighting me every step of the way. Had I not had past pleasant practice with Python, I would have abandoned the language as useless.
Finally, at the end of the week. I realised that I was trying to write Scheme in Python, which work about as well as writing Python in Scheme. Python has for loop and I should be using them.
About twenty minutes later, the app was ported. It wasn't my finest hour.
We took an app written and maintained for the last 10 years in language A, and re-wrote it from scratch in language B.
The new codebase is smaller, more maintainable, and runs faster!!!
A month ago I was in the same place- I would start reading a short blog posting on RNNs/ConvNets/etc., and within 2-3 paragraphs my eyes would glaze over from the math and other foreign terminology. Frustrating. To try and fix this I am "auditing" the Stanford course on ConvNets: http://cs231n.stanford.edu/syllabus.html
I'm about 2/3 done with the homeworks, and I understand this stuff now. I'll never be a data scientist, but I know enough to implement these networks on my own, and to understand blog posts like this. It's a lot of work for one course, much more than I remember from my own undergrad years. I had to revisit Calculus & Linear Algebra too. But if you're genuinely interested in this stuff you can pick it up.
"I had to revisit Calculus & Linear Algebra too" - what resource would you recommend for this? after being a web developer for a couple of years i find myself rusty and unable to find good resources for this.
Trying to get into machine learning but i've forgotten most of the math
I'm really looking forward to no longer having to figure out which project I have to axe to keep my "small" plan under the 10 repo maximum. That was always annoying.
