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Machine Learning. In 2018 I went from "zero to sixty", so to speak. At the beginning of the year I knew nothing about ML, and my math skills had gotten so rust
by dsiegel2275 8y ago
Machine Learning.
In 2018 I went from "zero to sixty", so to speak. At the beginning of the year I knew nothing about ML, and my math skills had gotten so rusty I couldn't even remember how to do simple derivatives or multiply two matrices.
In the first half of 2018 I relearned the college math that I had forgotten by working through MIT OCW's Linear Algebra, Calculus, and Probability courses.
In the Fall, I enrolled in Carnegie Mellon's 10-601 course, graduate "Introduction to Machine Learning". It was hard, it was a ton of work, but I did well and it was completely worth it as I now have a solid understanding of the basics of the field and can continue studying this upcoming year and into the future.
- p2detar 8y agoThanks a lot for the MIT OCW lectures hint! I want to do the same in 2019. What works for me in general is diving into a side project and learning by hacking, but I fear ML won't be susceptible to this approach.
- anotheryou 8y agofast.ai looks promising for just that
- p2detar 8y agoLooks pretty cool! Thank you.
- anotheryou 8y agoI just started it too :)
- Drdrdrq 8y agoI also learn by doing, and it works with ML too (dived into it last year, though I'm currently not doing it anymore). Find a project and jump... Happy learning!
- pvarangot 8y agoThe Linear Algebra OCW is great if you do all the exercise and read the book as you study. For Calculus it's not so great, though the ODE course is fine. This kind of courses from UPenn are really good if you need to refresh single variable, though I did an older version were all the courses were given together than I can't find in the current Coursera: https://www.coursera.org/learn/single-variable-calculus https://www.coursera.org/learn/single-variable-calculus
- dominotw 8y agocurious, what you are planning to do with the new knowledge
- hekillno 8y agocan non-CMU student learn that class online?
- senorsmile 8y agoI would like to know the same.
- dsiegel2275 8y agoNo, that specific class isn't available to non CMU students or staff (of which I am the latter). There are several CMU courses, however, where the full collection of lectures are available to watch on YouTube. The Fall 2017 offering of Mathematics for Machine Learning lectures are all on YouTube.
- yogeshp 8y agoProf Tom Mitchell's video lectures for 10-601 are available online: http://www.cs.cmu.edu/~ninamf/courses/601sp15/lectures.shtml http://www.cs.cmu.edu/~ninamf/courses/601sp15/lectures.shtml
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- mrfusion 8y agoWhere did you get that kind of motivation? Sounds almost super natural.
- dsiegel2275 8y agoIt isn't supernatural, trust me. Very simply: I set a goal, understood what prerequisites I needed to fill, and just worked hard to get there. I put in about 5 - 10 hours a week in the first half of the year working through the OCW courses, then probably 10-15 hours a week during the CMU class. I work fulltime as a software engineer, so my 'class' time was usually a couple hours a night, after the wife and kids go to bed.
- bruhbruhbruh 8y agoI struggle to focus after a full day of work and other tasks. I especially struggle to focus on technical work, and learning new things is difficult. How do you have the energy to sit down for another few hours of technical work after a full day of work?
- dsiegel2275 8y agoI'm not gonna lie, putting in those couple hours can just be plain tough. Some days it is the absolute last thing that I want to be doing at 9 o'clock in the evening. But I motivate myself by focusing on the long-term impact for my career, and thus the benefits for myself and my family: Coupling my expertise in software engineering with deep knowledge in an adjacent field such as ML I believe can open up new opportunities and give me the freedom to take my career along paths that weren't possible before. That is what I remind myself when I sit down to work homework problems late in the evening.
- masteruvpuppetz 8y agoThat's amazing :) What do you plan on using ML knowledge? Like does having this skill have a market (for non-PhDs)?
- petrbela 8y agoApplied ML is one of the hottest CS jobs these days :-) From startups to big cos, everyone's looking for data scientists.
- gcb0 8y ago> derivatives or multiply two matrices > college math Those should be high school on most places
- sedatk 8y agoYes, those are thought in high school in Turkey.
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- ilikehurdles 8y agoDerivatives were available for the most advanced level students in high school where I went. Even then it was understood that they were receiving college credit early. Linear algebra not at all.
- thealfreds 8y agoNot too much with linear but usually 10th or 11th grade math will introduce matrix multiplication.
- justwalt 8y agoWhich is odd, in my opinion. Linear algebra is easier than Calculus and would likely be more useful to the average person.
- ilikehurdles 8y agoAgree completely. In my university, calc was a pre req for linear algebra and it didn’t make any sense to me then either.
- lucb1e 8y ago> so rusty I couldn't even remember how to do simple derivatives or multiply two matrices. I was never taught how to do either of those things. Am I missing out on something?
- corysama 8y agoIf you want to do machine learning, those two ops are pretty much the foundation of how it works under the hood. If you want to do coding in general, I like to say that you can have a career in code without being good at math. But, math is how great coders do what seems like magic to other coders.
- jmkni 8y agoThat’s a really nice way of putting it. As a grown up who has already been working as a software developer for ~10 years, do you have any recommendations on books to read, courses to do etc if I want to improve my maths? I’m not terrible, but I know I could be a lot better!
- anpat 8y agoI was on the same boat as yours about 3 months ago and I picked up 3 books based on HN comments; 1. No bullshit guide to Maths and Physics [1] 2. No bullshit guide to Linear Algebra [1] 3. A programmer’s introduction to mathematics [2] I haven’t gone through the books completely but I’m halfway through the ‘no bullshit..’ books and I liked them based on how easy they were for me to approach. May be they also fit your learning style as well? Hope this helps and happy learning. [1] : https://minireference.com https://minireference.com [2] : https://www.amazon.com/dp/1727125452 https://www.amazon.com/dp/1727125452
- shriek 8y agoI'm same as you too but I did have some background in math from college but I've been rusty on them already. - I know it's said over and over again but KhanAcademy is pretty good for high-school math - For probability, I'm also going over this website[1] at the moment. Maybe someone else has other recommendations too - Linear Algebra is next on my list but others have given some reference for it already - Andrew Ng's course on Machine Learning from Coursera is also another frequently recommended if you are trying to learn math for it [1] https://www.probabilitycourse.com/ https://www.probabilitycourse.com/
- itprofessional4 8y agoOne course I found very helpful was 6.034 by Prof. Patrick Henry Winston[0] . Worth the time. [0] https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/index.htm https://ocw.mit.edu/courses/electrical-engineering-and-compu...
- wholien 8y agoWhen you say you enrolled in 10-601, what did you do? I assume you aren't actually a student at CMU.
- dsiegel2275 8y agoI'm a staff member at CMU, and so have the benefit of being able to enroll in classes for free.
- PascLeRasc 8y agoI'm also a CMU staff member and I audited 10-601 this past semester but had to stop halfway through because it was too over my head, props to you for doing well in it!
- mrsln 8y agohttps://news.ycombinator.com/item?id=18741229 https://news.ycombinator.com/item?id=18741229 - what do you think about this? Is it really pointless to learn ML unless you're going to work in a big company that have access to a lot of data?