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Machine Learning 101 slidedeck: 2 years of headbanging, so you don't have to
- catnaroek 9y agoThe slide titled “A note on dimensionality” reminded me of this xkcd: https://www.xkcd.com/547/ https://www.xkcd.com/547/ “That would be (very) bad.”
- hprotagonist 9y agoI was absolutely convinced by the title that this would be a link to a research blog post about an analysis of hair motion at metal shows.
- XR0CSWV3h3kZWg 9y agoI really wish that they hadn't decided on having moving images behind the text you are supposed to be reading.
- pruthvishetty 9y agoGold!
- minimaxir 9y agoThe presentation goes straight from from linear regression and classification to computer vision and reinforcement learning. The practical value of ML/AI is what’s in between and is something that isn’t often discussed between all the hype. ML/AI can be used to build models which work well with nontabular data (e.g. text and images), and can solve such regression/classification problems more cleanly. (and with tools like Keras, they’re as easy to train and deploy as a normal model)
- flor1s 9y agoI think slide 12 touches on this. Even in the case of an image we can process it pixel by pixel, but that would be lunacy! For text great results have been achieved using automatons, but they only work for structured strings and break if you add only a little bit of noise. I feel like ML should be considered whenever you feel like programming something requires you to deal with many different cases, you have a lot of example data available, and having some false positives / true negatives is not a big problem.
- deleted 9y ago[deleted]
- achompas 9y agoSorry, where do you see this? I see a lot of slides devoted to the "in-between" of random forests, perceptrons, etc. The jump from supervised to unsupervised to RL also makes sense, since RL is a different learning paradigm from the other two. I'm as exhausted of the ML hype as anyone else, but I believe this deck tempers expectations.
- rubenfiszel 9y agoIf I understand correctly those are slides from a Googler (Not sure if those slides have corporate approval), that probably have as a side goal to showcase that Google is a fun place to do ML. Not that I am judging or anything but, the author's personal website http://www.jasonmayes.com/ http://www.jasonmayes.com/ whose link is displayed multiple times is a giant ad to get hired elsewhere and show at least some desire for other career opportunities. Not sure if that reflects greatly on the company.
- zo7 9y agoGiven the number of plugs for Google products/projects/research (especially near the end) it's probably intended to be more of an ad for Google.
- auntienomen 9y agoMaybe. OTOH, this guy's resume says he's a web programmer. I'd think if google were recruiting people interested in machine learning, they'd get one of their machine learning specialists to write this.
- carlmr 9y agoSpecialists are usually the worst teachers, because they assume that you know trivial things. What appears trivial to them is not trivial to the audience though. https://en.wikipedia.org/wiki/Curse_of_knowledge https://en.wikipedia.org/wiki/Curse_of_knowledge
- npgatech 9y agoChecking his website, it reeks of narcissism. There are better ways to assert yourself than to do all the corny things he has done on his self promotion website.
- jasonkester 9y agoAre you honestly slagging a guy off for talking about himself on his resume??? I mean yeah, we computer folk are supposed to be all self deprecating and all. But if there is one place we should stop mumbling and talking ourselves down for a second, that is it. At some point if you want people to know what you do, you're going to have to tell them.
- nblavoie 9y agoThe document is awesome, but the animated backgrounds are distracting.
- ausjke 9y agoexactly, I stopped at the second slide because of that. "I ask for your undivided attention for two hours" is what it says, the background animation seems not helping that goal, quite the opposite.
- dkersten 9y agoCompletely agree. The movement in the animations keeps grabbing my attention. The first slide took multiple attempts to read without getting distracted. Maybe my attention span is just bad, but I really want to understand the slides! :(
- wooshy 9y agoAgreed, I couldn't get past the first few slides without getting annoyed by the animated backgrounds and closing the presentation out.
- dingo_bat 9y agoI tried to edit it to prevent animation and apparently I can't edit or copy or download or export. Gotta try printing next.
- Animats 9y agoLoading... Google Slides is really slow. That's why this needs two hours. Most of the real content is in linked videos.
- rkagerer 9y agoNot bad but toward the end it basically just becomes a big pitch for Google's ML products. It links to 3Blue1Brown's videos which are great!
- kmax12 9y agoAs someone who works with a lot of people new to machine learning, I appreciate guides like this. I especially like the early slides that help frame AI vs ML vs DL so that people can have a realistic understanding of what these technologies are for. For my part, one of the biggest realization I had after many years of applying machine learning was that I got too caught up in the machine learning algorithms themselves. I was often way too eager to guess and check across different algorithms and parameters in search of higher accuracy. Fortunately, there are new automated tools today that can do that automatically. However, the key piece of advice I'd give someone new to machine learning is not to get caught up in the different machine learning techniques (SVM vs random forrest vs neural network, etc). Instead (1) spend more time on translating your problem into terms a machine can understand (i.e how are you defining and generating your labels) and (2) how do you perform feature engineering so the the right variables are available for machine learning to use. Focusing on these two things helped me build more accurate models that were more likely to be deployed in the real world. Feature engineering in particular has become a bit of a passion of mine since that realization. I currently work on an open source project called Featuretools (https://github.com/featuretools/featuretools/ https://github.com/featuretools/featuretools/) that aims help people apply feature engineering to transactional or relational datasets. We just put out a tutorial on building models to predict what product a customer will buy next, which is a good hands on example to learn from https://github.com/featuretools/predict_next_purchase https://github.com/featuretools/predict_next_purchase for beginners.
- nl 9y agoThis tool is pretty interesting. I've been playing around with a similar idea of text. Do you already do that?
- xzzherculeszzx 9y agoWhat are best resources for "defining and generating" labels? Any recommendations?
- kmax12 9y agoI don't know of a definitive public resource for this. I published a paper in IEEE's Data Science and Advanced Analytics conference on it back in 2016. You can find that here: https://dai.lids.mit.edu/wp-content/uploads/2017/10/Pred_eng1.pdf https://dai.lids.mit.edu/wp-content/uploads/2017/10/Pred_eng... Additionally, my company (link in profile) builds a commercial product to help people define and iterate on prediction problems in a structured way based off of the ideas in that paper.
- candiodari 9y agoCool presentation ... but there's a million ones like this. We don't need yet another basic introduction to machine learning, we need detailed practical studies of real problems.
- mr_toad 9y agohttps://www.kaggle.com/ https://www.kaggle.com/
- gregorymichael 9y agoEasier to curse the darkness than to light a match.
- mmanfrin 9y agoGood slides, got me back in to the fever of wanting to learn; although a lot of the credit goes to the linked 3Blue1Brown videos (whose Linear Calculus series is excellent) which were a lot more technical but no less approachable. Question to those versed in ML: I want to work on an AI that plays a video game (aspirations of playing something like Rocket League, but I know I need to start smaller with something like an old NES game). I understand these are usually done with Recurrent Neural Networks, but I'm a little lost as to how to get data in to the RNN -- will I need to make another AI or CNN to read the screen and interpret (including the score?) My 30k ft view is that if I can define a 'score', give it a 'reset' button, and define 'inputs (decision targets)', then I just need to give it the screen and let it do its thing. But getting the 'score' is the part I can't figure out short of adding another layer to the classifier.
- allenguo 9y agoYou should check out Berkeley's deep reinforcement learning course[1]. There's lecture videos, slides, and homework assignments, and it's all very up-to-date. [1] http://rll.berkeley.edu/deeprlcourse/ http://rll.berkeley.edu/deeprlcourse/
- dicroce 9y agohttps://www.youtube.com/watch?v=PDbXPBwOavc https://www.youtube.com/watch?v=PDbXPBwOavc
- charlysl 9y ago"There is no golden road to geometry" If you really want to understand you would be much better off starting here: https://work.caltech.edu/telecourse.html https://work.caltech.edu/telecourse.html
- vowelless 9y agoSlide 64: A whole tonne of stuff going on in robotics right now. Just take a look at Boston Dynamics YT channel for some mind bloding research, most of which is driven by ML.. I highly doubt that BD is doing any ML work right now ... Can the author link to specific research that they are doing using ML?
- fnl 9y agoA bit extreme, but yes, saying that robotics is driven my ML is ... weird.
- natch 9y agoYou mean public work perhaps? I imagine they are doing a lot with vision, gait learning, object manipulation, task planning, autonomy, multi-robot coordination, etc. all of which can be enabled by or at least helped along by machine learning, no? Your request for links is valid, I just am surprised anyone would doubt that they are doing ML research unless you are thinking of a strangely narrow definition of ML.
- fnl 9y agoMost of robotics is about reinforcement learning. EDIT: Oh, and expert systems/rules. Lots of em. EDIT2: Well, an engineering, obviously... :-) Heck, just check Wikipedia on the topic...
- natch 9y ago>Most of robotics is about reinforcement learning. is != always will be. But forget that, let's check Wikipedia, as you suggest. What are the first few words of the article on Reinforcement Learning, hmm. The very first few words at the very beginning of the article: "Reinforcement learning (RL) is an area of machine learning..." Read that and tell me what the last two words are. "Machine learning."
- iamwil 9y agoAs I remember, they don't use any deep learning ML. I think their stuff is based on something about funnels.
- kbart 9y agoInformation is great, but it would be much more readable in simple text form or pdf. It's strange that senior creative engineer at Google doesn't know presentation making basics.
- quacker 9y agoIt's not surprising that a Google engineer would use Google docs. It's at least easily shareable and there are complementary embedded videos that aren't suitable for text/PDF anyway. Though, the options to export as a PDF didn't work for me (either via download or as an export to Google Drive). I'm assuming the presentation is too big.
- JepZ 9y agoSame here, just tried to download the PDF multiple times but it always failed (didn't even start; tested Chrome and Firefox)...
- qazpot 9y agoCan't download the PDF as well.
- ratsimihah 9y agoThis might be intended behavior. If you try to print the deck, it shows the Goole Drive access request page.
- dingo_bat 9y agoIt has been explicitly set to be non-downloadable or exportable.
- agumonkey 9y agoThe document has export feature disabled, but it doesn't change the viewer UI and there's no error message. I wouldn't mind google docs if it wasn't for the heavy animations ...
- ForFreedom 9y agoHow can I download this slide?
- natch 9y agoJust use the download button under the gear icon. /s Unfortunately it doesn't work I guess. Oh, and he says he is watching you... Maybe he really means this? Maybe that's why he disabled downloads?
- ForFreedom 9y agoI clicked the gear I clicked the PDF/ PPTX nothing seems to be happening.. I think, I just became "Person of Interest"
- natch 9y agoYep same here.
- trishmapow2 9y agoGoing to the /export/pdf link shows access denied. My quick 3min workaround was to use FF dev tools, settings enable screenshot, click through and save each page.
- agumonkey 9y ago96 x 2 clicks too such modern
- iamwil 9y agoWhat was he headbanging about in these last 2 years? Just a linkbait-y title?
- AdReVice 9y agoWhy is the file protected.. how to access it
- donkeyd 9y agoI created nearly the same presentation this week. It's good to see that I didn't miss much, though this one goes deeper, which I don't do on purpose. I'll probably send the attendee this presentation afterwards for those who want to go deeper, very cool!
- elephant_burger 9y agoThank you for this. This is an excellent slide deck
- TheNewLab 9y agoNice introduction, but I really don't see how "2 years of headbanging, so you don't have to" applies.
- pimlottc 9y agoI think the author meant "banging my head against the wall" while getting it all working but didn't realize the term has a very different meaning...
- levesque 9y agoThere is no quick way to get a good grasp on ML. You just need to spent the time needed to get there, reading and working on simple problems, carefully validating that you understand concepts as you go. It's like asking for a way to learn mathematics or computer programming in an hour. Hint: there isn't.
- Jaruzel 9y agoReading normally, and skipping the videos, the whole deck takes about 15 minutes. The last 3rd of the slides are basically promotional material for the various Cloud ML services that are out there. It's nice deck, but I'd hoped the blue slides went more technical without dropping out to various videos. If wanted videos, I'd go to youtube directly. Not everyone wants to learn through watching people talk. I learn best when I read, it's unfortunate that youngsters these days think that the written word is now a poor cousin to flashy video. <rant> In the same way that new clothes are no longer for me, and new music is no longer for me, and all good TV shows and films are full of people half my age, I also now feel that I'm being aged off the internet. I was here first, you young whippersnappers! It's MY lawn. </rant>
- mrweasel 9y agoI honestly don't really see the value in a slidedeck, without the accompanying talk. It's the same as when someone proclaim: "Slides from this talk is available online", yeah that's not really any good without video or audio.
- minikomi 9y agoIdea: Neural network generated infinite sidedeck which appears to follow a coherent narrative, which is ever so slightly out of grasp.
- nerdponx 9y agoDisagree. Slides, even out of context slides, can be an excellent source of information for people new to a field: they still give a sense of the structure of the talk (what is related to what), and they give you keywords to start searching for. And for experienced readers, sometimes they just contain nice ideas or tips you had not been aware of.
- cyberpunk0 9y agoNo they aren't. Slides are a skeleton. Just bullet points that 99% of the time offer no usable information
- fartcannon 9y agoThis ends up not being much more than an advertisement for google. Wikipedia's articles on these subjects have more depth.
- tudelo 9y agoPretty similar information to my semester-long Machine Learning class in undergrad (with less detail). Good information to get the basics down, but can't say I've gone to apply any of the information I have learned yet... Still a useful set of slides.
- philyalater 9y agoAs someone who has recently taken an interest in machine learning and AI, this deck is much appreciated.
- mtw 9y agoThis make it look like all interesting ML projects are by Google.
- tziki 9y ago>Artificial neuron (aka perceptron) These aren't synonymous, a perceptron is a type of artificial neuron. Also confusingly, 'multi layer perceptrons' might not contain perceptrons at all.
- swframe2 9y agoProbability distributions are approximate world models. There are mathematical tools to management them. Once you see the world this way, ML/DL becomes more intuitive.
- bitamess 9y agoI really appreciate you sharing this, as myself always try to create a learning path and make things clearer as much as possible on top of it, slides are good looking (design awesome). the problem sometimes comes is at its overwhelming when advanced things pop up in talk and its hard to know what should we listen to it or is it above our level of the current situation.
- cerealbad 9y agostrobe morphing advertisements that are trained to adapt to your unique reaction(s) until it detects the same facial response as the last time you made a purchase. botox, masks, camouflage tattoos, permanent smiling, IR obscurants. the arms race begins a new. benevolent dictatorship by self regulating machines is probably going to plague us for several thousand years. wouldn't that be interesting, if the last evolutionary bottleneck is getting smart enough to create an enclosed planetary system that fully satisfies your biological needs and suppresses all intangible ones so there is no reason to go any further up the chain of exploration. stopping death means stopping life, every generation is more forgetful of the past than the last. the light ages will be far more destructive, what could possibly motivate you to stop a perpetual pleasure machine? how do you prevent the inevitable conflict between those who insist pain and suffering is an essential part of the human experiment and those who just force them to feel good and change their mind? what will happen to these toddlers in 10-15 years? they will have grown up interfacing with some electronic device for every single day of their young lives, a different type of consciousness shaped by destruction of self-confidence in their own knowledge and memories and a complete trust in the needle-finders of big hay. this shift will be as important as pre-writing to post-writing, except the transformation won't take centuries and millennia to propagate itself across the planet. a post-memory world, with every human enslaved by their base sensations. the first US president who is an internet addict. "[Writing] will create forgetfulness in the learners’ souls, because they will not use their memories; they will trust to the external written characters and not remember of themselves. The specific which you have discovered is an aid not to memory, but to reminiscence, and you give your disciples not truth, but only the semblance of truth; they will be hearers of many things and will have learned nothing; they will appear to be omniscient and will generally know nothing; they will be tiresome company, having the show of wisdom without the reality." the future is a fate worse than death.
- bpizzi 9y agoThat's a strongly pessimistic view you got here. Are you aware that there's people thinking the opposite of you? The thing is: the reality is always far more balanced that what the extremists are preaching us.