Hacker News Reader

This course was discussed here on HN 3 months ago: https://news.ycombinator.com/item?id=13224588

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 )

The course is excellent, and thank you for making it and offering it for free - but a word of caution for those considering following it: Along the way you will incur not-insignificant costs for Amazon EC2 GPU instances, and, even if your instance is shut down, SSD EBS storage costs.

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.

Yep, the course is free, but you'll need to pay for the computing power one way or another.

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.

What's the minimum nVidia GPU spec (VRAM) and SSD/HDD disc space (TB) required, from your perspective?

Get a GTX 1070 at a minimum. GTX 1080 Ti if you have a bit more cash to spend. Disk space is entirely dependent on your data set size. We're not talking huge numbers for most things you would be doing

I have GTX 970 and how much spare space do we need?

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?

The install-gpu.sh script found in fastai's github can be used to set up the required environment on an Ubuntu box.

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.

To give a more exact estimate - if you don't use spot instances ($0.20/hour) it'll cost $0.90/hour, and if you do the suggested 70 hours of work for the course, that's $63. And then there's around $6/month cost for the EBS volume.

Not exactly.

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'm going through this course, but using Google cloud instead of AWS. I can confirm that at least the first Jupyter notebook works well for me.

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)

Any chance you can share the adapted scripts? I assume they are easy to make, but the less barriers to entry the better.

Sure:

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...

Buy a laptop with a GPU. If you are serious about learning AI, it's worth spending few hundred dollars to get a proper workstation.

I heard that nowadays it's possible to buy a laptop and a external GPU?

I have a mac, is it possible to really buy an external GPU??

Yes, but GPUs should only be consider for acceleration when there is insufficient local CPU power to accomplish something valuable. Otherwise, it's like buying a Ferrari to get groceries.

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

There's been some work on using AWS spot instances for the course, which can save quite a bit:

https://medium.com/slavv/learning-machine-learning-on-the-ch...

http://wiki.fast.ai/index.php/AWS_Spot_instances

Like how much? If you are going to get into deep learning for real seems like it might be worth building a multi-GPU workstation?

Don't buy equipment before you have demonstrated a real need for it.

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

>Gonna learn electronics - buy oscilloscope

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.)

I've certainly solved problems with a storage scope before, but not for a long time, and they were mostly software problems rather than hardware problems (ie. using it as a poor man's logic analyzer to infer what's going on with the code via a couple of spare IO pins). I really kinda want one though.

There is actually an accepted term for what you describe in many circles, called GAS -- Gear Acquisition Syndrome.

One forum user put together a <$700 complete PC with an adequate GPU. You definitely don't need >1 GPU.

Or you can use spot instances, as a sibling comment mentions - about $0.20/hour generally.

Ah, cool. I am familiar with AWS and spot instances, but after that comment was assuming it required multiple instances for training or something.

Build a fast deep learning machine for under $1K https://news.ycombinator.com/item?id=13605222 a month ago with many tweaks recommended in the comments.

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

I'd consider $60 bucks to pick up deep learning skills an "insignificant cost".

Well, that depends on how you define your cost function. :-)

"Along the way you will incur not-insignificant costs for Amazon EC2 GPU instances"

Is there some particular constraint involved that I cannot run the computations at home?

Heat death of the universe.

Buy a pc/laptop with an NVIDIA GPU and setup Linux on it. It is a better option than using EC2 instances.

How much VRAM is required?

While I have found it quite easy to take a code-first approach to deep learning/machine learning, I have encountered a lot of scepticism from existing ML/data science practitioners about such an approach, and I feel like investors will be even more risk-resistant.

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.

Hard to say. Universities aren't very good at instilling good applied engineering. If you are 18, very high GPA and you've passed this course and have strong programming skills, I think some investors would be interested. Similarly, if you have say a physics degree from a good university and you've done this I think investors would be interested.

If you're 22+ with a high school degree and not much of an engineering resume... Yeah, your pitch deck better be good.

Besides graduating from your fast.ai course, what were the other qualifications of those Google Brain applicants? I'm imagining they would have, or be in the process of getting, an MA/PHD in non-AI-related area.

No, the person I know who is in the last round is an economics major with no Masters/PhD. She has a very impressive background in industry.

Although a lot of folks in the course do indeed have graduate degrees in other fields (including English Lit, Neuroscience, Radiology, etc...)

I am sorry if I sound rude or naive or both.

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.

My $.02 -- if I were to provide a resource with the goal of being of great value to people, and it's within my wherewithal to maintain it with what I make elsewhere, the $$ return from ads are far too low to justify how much they detract from the experience I set out to provide. Ads aren't the absolute worst, but I think we can agree they are on average negative to the experience you visit a non-shopping page for.

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.

True, what made me write it was a YouTube channel I came across, they don't accept donations or show ads on their channel and they have crazy views, they say that we don't want to earn money on this, granted that they give it away for free, but it isn't "evil" to get some money out of it, I am not saying rip off students by charging 10000$ per session, but providing something like a PDF version of the online guide for a small amount say $5 would, in the long term, give you some return.

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.

Ads are basically a tool for psychological manipulation. It's unfortunate that this is the only practical method of monetization for some creators. Micropayments in future may help with this. To me, ads do feel disrespectful of my audience.

While ads might be that, but all I wanted to say is that it could be monetized somehow like a pdf on leanpub for 0-20$ pay what you want, I would have gladly paid.

I'm pretty new to AI -- would it be better to do this course or the machine learning course by Andrew Ng on Coursera?

The Coursera course is "machine learning", which is a more general terms, while this course (based on the description) is "deep learning", which is more specific - the ML course ends with Neural Networks, while this one starts with them.

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.

Could you add a simple description of the practical usecase for the lessons? I know what "image recognition" is useful for. I have no idea whether I need to or want to learn "CNN", "overfitting" "embedding" "NLP" or "RNN". I am interested mostly in image recognition and text classification.

Thanks for putting that up. I'm gonna try to find the time, since I'm hoping to do a PhD someday.

Thanks, I look forward to going through this course.

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, ...

Some learning resources:

Learning AI Advice from Open AI, Facebook AI leaders

https://medium.com/@allenleein/recommended-resources-for-lea...

Thanks! Thanks, thanks, thanks a ton for what you are doing. As someone without a strong math background, it is kinda hard to enter the field, so I'm going to take 7 weeks now and hope I can understand deep learning better than I do now.

Checkout https://www.floydhub.com as a replacement for AWS!

This might be exactly what I have been looking for... thanks!

I wonder if the AI/machine learning revolution will open new jobs for people coming from IT admin roles.

Came here expecting to see this mentioned somewhere, was not disappointed :)

Thankyou, this looks to be exactly what I need! Starting the course now.

Thanks so much for highlighting this!

thank you .. your course was really helpful.

Thank you

I love your project but I totally detest your landing page with the huge animated panels that sit there eating up cycles that could be used for something better. I'm sure it's great for conversion and all that but that doesn't stop me from being irritated.

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.

"that sit there eating up cycles"

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.