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Andrew Ng updates his Machine Learning course
- xwdv 4y agoAlthough this is the best course on ML, is it really practical for anything? Has anyone built products for things they’ve learned from this course?
- UmbertoNoEco 4y agoNo. The ugly truth is that these courses will be useless to 99% of the people. Machine learning is dominated by big corporations with gigantic amounts of data and processing power. If you want to work in one of them or create competing ML companies you need pedigree (a PhD from a well know university), and those guys arent taking courses with fake credentials. You could use ML in your job/company but then you dont need this course, you just use a ML product. See this course as a hobby thing, or if you are in HS and want to start preparing for college, otherwise there are better uses of your time.
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- woah 4y agoYou can get almost unlimited GPU time on Google Colab for $50 a month. I don't know why or how they pay for this, but it does bring "real research" into the reach of individuals.
- UmbertoNoEco 4y agoYou can get more processing power and true unlimited time with any semi-competent graphic card (probably costing less than 1 year of Colab Pro+). Pro+ is a scam, you are not told what kind of instances you will be running at, and you dont have any guaranteed continuous running time. And even if you were given full 24/7 access to a top of the line card that would be like 0.001% of the power used to train any big modern ML model. Users complain all the time: https://www.reddit.com/r/GoogleColab/comments/sq0lia/colab_pro_my_experience_so_far/ https://www.reddit.com/r/GoogleColab/comments/sq0lia/colab_p...
- queuebert 4y agoOr maybe people want to understand what's going on under the hood of the ML products they use?
- asey 4y agoOf course, though in fairness parent was answering grandparent's specific question (and accurately in my experience)
- Tenoke 4y agoThere's a lot of ML happening outside of big corporations, which you can confirm by just searching 'machine learning' on any job site. While it's true that often you can use ready-made ML solutions, you often will benefit from additional knowledge for improving or adjusting them for your company's specific problem and while interviewing you will often be asked the kind of questions those courses cover.
- mupuff1234 4y ago> You could use ML in your job/company but then you dont need this course, you just use a ML product. ML product?
- benrow 4y agoFor example, Google Vision API can do some out-of-the-box classification on arbitrary images with no training needed. Covers super common cases such as explicit content detection and object detection. There are more customisable products within Google where you can provide training examples and labels using a UI (AutoML I think it's called). The result is an endpoint you can use to do inference, based on the model created behind the scenes. I just mention these examples because I've spent a little time researching them at top-level.
- sydthrowaway 4y agoHow about joining FAANG as SWE, and then internal transfer?
- lupire 4y agoLike the other 10K employees at the company with the same idea?
- MafellUser 4y agoI took this course as a defensive mechanism against BS at work, especially when the consulting Data Scientists were around. In that sense it's super practical. ML is dominated by gigantic datasets and massive computing powers, something individuals will not have a lot of.
- austinjp 4y agoCan you explain a little more about how and why this was practical?
- Choco31415 4y agoI used it to help learn ML before I could start taking the classes at my university and it was enough to land me a research position at the Air Force. Admittedly I also bought textbooks and worked through tutorials as well.
- NelsonMinar 4y agoI thought it was useful but awfully low level. For example I hope to never, ever implement backpropagation again; I'm going to use whatever code is in TensorFlow or PyTorch or whatever. But as a student I'm glad I did implement it myself, once, so I understand what is going on. More broadly it demystifies the black box of machine learning methods and you can see it for the giant pile of statistical categorizing functions that it is. The most practical takeaway I got from Ng's course was the dangers of under and overfitting your data and techniques for detecting when you make that mistake.
- ghaff 4y agoI still remember a talk by a woman from Google at a fairly long ago now O'Reilly conference (R.I.P). Part of what she discussed was Research AI vs. Applied AI. The gist of it was that a lot of the things in university course, graduate programs, etc. are tilted towards Research AI and you can get away without a lot of that stuff by using pre-built tooling for practical machine learning applications. Of course, you want to have some understanding of what's going on under the covers but, for a lot of people, starting from first principles is quite hard and isn't really necessary.
- vasili111 4y agoIs the knowing only Algebra I enough for this course?
- NelsonMinar 4y agoNot the course I took. It relies on basic linear algebra like matrix multiplication. You can probably get through it with just coding and not understanding the math but it wouldn't be much fun. Not sure about the new course.
- aaaaaaaaaaab 4y agoIn 2012 I did Andrew's original machine learning course, and implemented a bespoke OCR engine for iOS, which was released in a banking app for scanning utility bills. Back then deep learning was just taking up, so I did my own backprop training in Matlab based on Andrew's code as well. It was a pretty fun end-to-end experience, much better than just throwing stuff at tensorflow like we do nowadays.
- vasili111 4y agoDo you thing now days Deep learning does not requires much math? If yes, to what extend of knowing math is enough to be truly good deep learning specialist? By deep learning specialist I mean the person who is building a commercial software that uses deep learning but not tools for deep learning.
- rg111 4y agoOh yes. The things I learned here helped me gain a solid foundation, which, in turn helped me learn Deep Learning. And Deep Learning feeds me now. The good thing about this course is that it is not Math-shy. It is not rigorous in terms of Math, like there are no proofs and so on. But Math is omnipresent here. Andrew Ng's MOOC is among the best game in town. Ng is among the best teachers I have ever seen.
- screye 4y agoThat's like asking if a CS101 course is useful. It is unlikely that you could build a major product with it, but it could tech you neat tricks to speed up some parts of work. Also, similar to cs101, it is a necessary first step towards a career in ML. So might as well do it. I know a bunch of business analysts and data analysts who have gotten a job based on what they learnt in this course. Ofc, they also got some stem degre alongside it, but this course made a difference.
- pm2222 4y agoI finished machine-learning[1] long time ago and it's so good. Look forward to this [2]. [1] https://www.coursera.org/learn/machine-learning/ https://www.coursera.org/learn/machine-learning/ [2] https://www.coursera.org/learn/neural-networks-deep-learning/ https://www.coursera.org/learn/neural-networks-deep-learning...
- rg111 4y agoThe only downside of [2] is that is is taught in Keras + Tensorflow rather than PyTorch.
- bitL 4y agoSo what, concretely, has changed?
- criddell 4y agoDoes anybody know if it is still free? I took this course and Dan Boneh's cryptography course and both were truly excellent.
- dwallin 4y agoThey say you can "audit" the course for free, but they employ a ton of grey patterns to get you to pay for it. I haven't been able to find out where to audit it yet. Update: You have to go into the individual courses within the specialization and the enroll popup will have an audit option. First Course is here: https://www.coursera.org/learn/neural-networks-deep-learning?specialization=deep-learning https://www.coursera.org/learn/neural-networks-deep-learning...
- rahimnathwani 4y agoIIRC you need to pay if you want your assignments to be (auto-)graded.
- cheriot 4y ago^ this has been the case for other Coursera classes I've done recently
- redox99 4y agoThat link says "Enroll for Free" and no audit button. Maybe it's because I'm not logged in?
- zerkten 4y agoSelect Enroll and then the dialog has the audit option at the bottom.
- rg111 4y agoAll videos of all courses in Coursera are free. You can watch them fully without providing your credit card info. There are two types of courses in Coursera- free and paid. In case of the paid courses, you can go to the course and navigate to the "Buy Subscription" page and click on "audit the course". You can watch all the videos for free, but you don't get access to quizzes and programming assignments (you never know what a web search will turn up ;)) ⊕. You do not get a certificate by completing a course or completing all courses of a "Specialization". In the case of a free course, you get access to all the videos, quizzes, and assignments. You don't get any kind of certificate. Instead of going to subscription page, you can just click "Enroll" and choose the no certification option. There are some great courses in the free tier (videos + assignments, no certs) as well. Dan Boneh's Cryptography and Grossman's Programming Languages A, B, C come to mind. Also Model Thinking by Scott Page. There were some great discussions on HN in the past. [0][1][2] ⊕ There are courses where duplicates of paid assignments and quizzes are provided under "Practice Assignment" as opposed to "Graded Assignment". Like Martin Odersky's Functional Programming Principles in Scala MOOC. [0]: https://news.ycombinator.com/item?id=25245125 https://news.ycombinator.com/item?id=25245125 [1]: https://news.ycombinator.com/item?id=16745042 https://news.ycombinator.com/item?id=16745042 [2]: https://news.ycombinator.com/item?id=22826722 https://news.ycombinator.com/item?id=22826722
- cypress66 4y agoChecked if he moved it away from Matlab, and yes he did! That's what steered me away from his course.
- quux 4y agoWhat's the class using now?
- oogetyboogety 4y ago10 bucks says it's python
- rashkov 4y ago“Graded assignments and lectures have been rebuilt to teach in Python instead of Octave“
- lern_too_spel 4y agoThe programming assignments were one or two lines in Octave. They'll turn into 10 lines of Python with indentation errors. Python is a worse pedagogical language for any course in applied linear algebra.
- adamsmith143 4y agoBut it's the language dujour for ML and in particular Deep Learning so theres no point doing it in any other language.
- beckingz 4y agoIt's amazing how hard it is to stay up to date in the data space, so it will be interesting to see how this course has been updated.
- farzatv 4y agoThis is one of the best courses on ML.
- smnrchrds 4y agoWhat are the others? Any recommendations?
- _odey 4y agoNot a full course I'd say, but I've used this one to learn the math behind deep neural networks and code my own from scratch in elixir and C: http://neuralnetworksanddeeplearning.com/ http://neuralnetworksanddeeplearning.com/
- lagrange77 4y agoYes, this is really good! Andrew Ng, too.
- vasili111 4y agoWhat is required math for starting Ng course?
- _odey 4y agoCan't tell you about Andrew Ng's coruse as I haven't done that, but for Michael Nielsen's course it was Matrices and Partial Derivatives. I'm assuming it's quite similar.
- UmbertoNoEco 4y agoDepends, how much linear algebra, probability and python do you know?
- samstave 4y agoWhat if one knows zilch, like my teenager... What might be best to start the path?
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- octagons 4y agoIs the registration broken? I am getting errors to "Please complete this required field" on two fields that I cannot see (or fish out of the div soup that is this signup page.)
- kache_ 4y agoReally great course, highly recommend it. It demystifies so much :)
- colordrops 4y agoIf one is a seasoned software engineer, but has little experience in ML or deep learning, is this course still suitable?
- vitorbaptistaa 4y agoDefinitely. It starts from first principles, linear algebra, and goes from there. It's an amazing course.
- vasili111 4y agoSo you need to know Linear algebra to understand? I knowing Algebra I enough to understad it?
- kache_ 4y agoIf you remember highschool AP math, you're good. Otherwise, check out ISLR for a faster intro, capped by your ability to read
- vasili111 4y agoDo you think ISLR is not outdated? I just looked at the date of publication and was wondering if it is still relevant.
- deathtrader666 4y agoWhy would Statistics, a branch of mathematics, become outdated in a few years?
- AiFoGhost 4y agoVery very excited to check this out.
- laurex 4y agoThough I had almost zero ways I would actually use the learning from this course (and indeed really never did any ML after and have probably forgotten it all) it was still a really fun brain exercise to revisit some math and then see how ML thinking worked! I have recommended it quite a few times.
- melling 4y agoAnnouncing that he updated his course certainly gained more attention than saying it will be available in June https://news.ycombinator.com/item?id=31204055 https://news.ycombinator.com/item?id=31204055 I certainly was excited when I saw this headline. Thought maybe it was early
- xtracto 4y agoI took this when it was mlcourse along with the aicourse by Peter Norvig. I was in research at the time. They were entertaining, but certainly mainly an intellectual curiosity for both academics and practitioners. Nowadays Practitioners would most likely use an ML library.
- karaterobot 4y agoI'll say that that waitlist registration form is very sketchy. Agreeing to receive marketing updates is required to join a waitlist for a course? Classy move.