thrawy45678: I see a lot of criticism about tmux and other non-core items being included in the overall curriculum. I think the author is trying to portray the workflow he is currently on and exposing the full tool kit he uses. I don't think he is saying - this is "THE" approach one has to follow.
derekmcloughlin: If you've no experience with ML stuff, you might want to start with Andrew Ng's course [...] Paperspace (https://www.paperspace.com/ml) have ML instances starting at $0.27 per hour.
webmaven: Any recommendations for the cheapest (but not "penny wise, pound foolish") HW setup that meets these requirements for course completion? - (answers: https://news.ycombinator.com/item?id=13227437 )
Edit: To be clear, I'm not suggesting it's not worth it, just highlighting that theres's more than a time commitment to budget for.
If you have a workstation with a fairly recent Nvidia GPU (I used a GTX 980 TI) and bunch of spare disk space, you don't need AWS at all. You'll still pay for the electricity, of course, but it's not what I would call a significant extra cost. That is, if you already have the hardware.
btw, I have a doubt, the course has specific video to setup aws, for local machines, what to do? should I install the required packages python, keras or whatever they use?
A GTX 970 should do. The exercises are designed for GPUs with more memory, so you'll need to use smaller batch sizes here and there.
The time you spend on the course, and the time spent by your instance running workloads are two completely separate things.
Your cost per-hour is accurate (plus a few bucks for an IP address), but the number of hours is off by an order of magnitude.
Also, I'm paying double that per instance per month for SSD using the provided scripts to build the instances. It's the smallest part of the cost, but I mention it because it can take newcomers to EC2 by surprise if they have an instance shut-down but consuming disk space.
I had to adapt the aws-install.sh script, but it was easy enough. I ended up using a snapshot instead of a persistent volume, as the monthly cost when you're not running is much cheaper. So I have a script to create a new instance and then restore that snapshot. It's faster than installing the dependencies each time).
Google Cloud has a $300 free trial for new users: https://cloud.google.com/free/
(Disclosure: I work for Google, but have no involvement in Google Cloud other than being a happy user)
1) Create the instance the first time: https://gist.github.com/rahimnathwani/40ed3b6f496d377e3d17de...
2) SSH into the instance and run this script (replace anaconda mirror if your instance isn't in Asia, and definitely set the password hash): https://gist.github.com/rahimnathwani/b63ebc5900b832743d9e22...
3) After you've tested the server, snapshot the disk (using the web console) and destroy the instance and the persistent disk.
4) Run this script to recreate the instance and disk from the snapshot (replace with your snapshot name): https://gist.github.com/rahimnathwani/9019df33d4ad7ec4607413...
https://www.journaldulapin.com/2014/12/04/a-nvidia-maxwell-c...
https://tompaw.net/cuda-on-thunderbolt-egpu/
http://xlr8yourmac.com/tips/MBP_ThunderBoltVideoCard.htm
AKiTio Node | Thunderbolt3 External PCIe Box for GPUs https://www.amazon.com/dp/B06WD8KS52
Gigabyte GeForce GTX 1080 XTREME Gaming Premium Pack Video Card (GV-N1080XTREME-8GD Premium Pack) https://www.amazon.com/dp/B01HHC9Q3U
https://medium.com/slavv/learning-machine-learning-on-the-ch...
This applies across basically all of life, and it's so frustrating to see people ignoring it, because what ends up happening is they use a string of 'gonnas' to justify buying stuff they don't need. Gonna get fit - buy $1500 worth of gym gear. Gonna learn electronics - buy oscilloscope, power supplies, tons of components. Gonna get your motorcycle license - buy brand new bike and stick it in the garage.
If you have a desktop computer, you're good to start. When you've done enough that your available CPU/GPU is limiting you on your own projects (not on something you pulled off github) then you can look at upgrading.
/rant
A fairly accomplished electronic engineer told me that they'd never once solved a problem using an oscilloscope, but that it helped to keep them occupied while they were mulling over what might have gone wrong. (That's presumably why the better ones have so many knobs and dials to play with, like one of those children's toys.)
Or you can use spot instances, as a sibling comment mentions - about $0.20/hour generally.
gcp: Contrary to the claims there, the CPU does matter
dsacco: yes, this will work, it will quickly become suboptimal [...] as you scale your hobby into something resembling more professional work
brudgers: I'd start with a used Dell Precision T7xxx series off of Ebay for a <$300 including RAM and a Xeon or two.
croon: If the limit is a firm $1000, I would get something like this: https://pcpartpicker.com/list/XHV9Fd
Is there some particular constraint involved that I cannot run the computations at home?
Funnily enough big tech companies have seemed the most willing to accept people making a switch. I'm guessing because their appetite for ML/DL people is currently unquenchable.
If you're 22+ with a high school degree and not much of an engineering resume... Yeah, your pitch deck better be good.
Although a lot of folks in the course do indeed have graduate degrees in other fields (including English Lit, Neuroscience, Radiology, etc...)
But I really do not understand why we hate ads. I have seen many tutorials which are given out for free. Of course, I am grateful that you decided to offer the course for free of charge, but I really would not mind a little adverts just to get you as the creator/maintainer some $$.
I am a self published author of a decent intro to web development book in Go language, it is an example driven tutorial/ebook and while the main book is open source on Github, there is a leanpub.com version which I offer for variable pricing, 0$ to 20$, and it has been working great for me, rather than getting nothing for the tutorial, I am getting something.
Without ruining the current tutorial, there are ways of getting something from it, of course.
For a fairly niche resource such as this (it'll never reach a "how do I get a boyfriend" level of audience), it's unlikely to ever draw as much ad revenue to pay for itself. To do so, a high quality, specialized ad system would need to be deployed, which honestly becomes a high touch deployment and maintenance project, that isn't directly tied to the core goal of just providing an awesome resource publicly for the greater good, which is just distracting (or costly) for whoever is behind it.
I appreciate the mature choice to not try to gain small change and instead eat the cost for hosting and development to feel good that you are providing something not just great, but unadulterated as well.
That's passive income which you don't have to bother about, like you'd have to bother about ad deployment. We as an industry are funny, we expect everything to be free of cost _and_ the author should not monetize it in any way possible, it isn't evil to monetize that's what I am saying.
I'd start with the Coursera one, if only to learn when _not_ to use a neural network and use something simpler. But if you already know how to cluster data with K-means, what a linear classifier is, and/or what an SVM is, then you can probably skip the ML one.
I wanted to point out though, that on the main page http://course.fast.ai/ the courses appear out of order; 1, 2, 0, 3, ... instead of 0, 1, 2, 3, ...
Learning AI Advice from Open AI, Facebook AI leaders
https://medium.com/@allenleein/recommended-resources-for-lea...
If the course is free and you're doing this to improve the world what's the point of using such tactics? At least shut down the rotation after one or two iterations.
Sure, about as much as rendering a single glyph of the entire text on the page.
Kidding - I have no idea but if it's just panning it that should be the ball park for the necessary compute load.
We don't charge anything for the course and there are no ads - it's a key part of our mission so we give it to everyone for no charge: http://www.fast.ai/about/
And yes, it does work. We have graduates who are now in the last round of applications for the Google Brain Residency, who are moving into deep learning PhDs, who have got jobs as deep learning practitioners in the bay area, etc: http://course.fast.ai/testimonials.html . Any time you get stuck, there's an extremely active community forum with lots of folks who will do their best to help you out: http://forums.fast.ai/ .
(Sorry for the blatantly self-promotional post, but if you're reading this thread you're probably exactly the kind of person we're trying to help.)