Gilbert Strang's New Course on Linear Algebra+ for ML Now Online • Hacker News Board

Re: Gilbert Strang's New Course on Linear Algebra+ for ML Now Online

#21

Post by idiliv » Fri, May 17, 2019, 3:57 PM UTC

saboot wrote: post #5

melling wrote: post #3

I skipped to the end and watched Alan Edelman’s talk on Julia. https://youtu.be/rZS2LGiurKY Alan (co-author of Julia) mentions that only Swift and Julia make the cut for ML, according to Google. I do like Swift and I’m willing to learn Julia, but most of the ML I see uses Python. Is there any traction for Julia or Swift, or is it mostly aspirational at the moment?

Can anyone comment on how well developed the CUDA support is on Julia? Compared to Python? I'm using Python/Numba for my scripts.

From my experience (and this seems to be a general trend with Julia projects) CUDA support in Julia - is not completely stable - is very fast moving - has a low learning curve - is highly amenable to your own tweaks and hacks

Re: Gilbert Strang's New Course on Linear Algebra+ for ML Now Online

#22

Post by localhost » Fri, May 17, 2019, 4:03 PM UTC

netwanderer3 wrote: post #16

I love how the introductory video gives you a big picture of different ways the math can be applied to real life scenarios. I wish they did this more frequently at school. Often the students did not understand at the beginning how all these stuff could be useful and thus they did not invest in the effort or were not interested at all. Each curriculum at school should have an introductory course that clearly outlines…

+1. Motivation is perhaps the most important aspect of teaching. I find that lectures are a terrible medium for teaching a concept; I find that I need time for quiet contemplation / practice / experimentation to truly understand something. However, lectures are fantastic for motivation and encouraging me to do the extra work on my own.

I've been reading (along with my kids) Ben Orlin's Math with Bad Drawings book which is great at motivating and presenting math in interesting ways that are all about presenting things as an interesting puzzle to be solved vs. the way much of math is presented in a rote "this is the algorithm / solution" way.

https://books.google.com/books/about/Math_with_Bad_Drawings....

Re: Gilbert Strang's New Course on Linear Algebra+ for ML Now Online

#23

Post by cwt137 » Fri, May 17, 2019, 4:07 PM UTC

melling wrote: post #3

I skipped to the end and watched Alan Edelman’s talk on Julia. https://youtu.be/rZS2LGiurKY Alan (co-author of Julia) mentions that only Swift and Julia make the cut for ML, according to Google. I do like Swift and I’m willing to learn Julia, but most of the ML I see uses Python. Is there any traction for Julia or Swift, or is it mostly aspirational at the moment?

Fast.ai is considering switching to Swift for future courses[1]. Could we be seeing the beginning cracks of Python's dominance in the ML space?

1) https://www.fast.ai/2019/03/06/fastai-swift/

Re: Gilbert Strang's New Course on Linear Algebra+ for ML Now Online

#24

Post by nexus7 » Fri, May 17, 2019, 4:55 PM UTC

cwt137 wrote: post #23

melling wrote: post #3

I skipped to the end and watched Alan Edelman’s talk on Julia. https://youtu.be/rZS2LGiurKY Alan (co-author of Julia) mentions that only Swift and Julia make the cut for ML, according to Google. I do like Swift and I’m willing to learn Julia, but most of the ML I see uses Python. Is there any traction for Julia or Swift, or is it mostly aspirational at the moment?

Fast.ai is considering switching to Swift for future courses[1]. Could we be seeing the beginning cracks of Python's dominance in the ML space? 1) https://www.fast.ai/2019/03/06/fastai-swift/

"The combination of Python, PyTorch, and fastai is working really well for us, and for our community. We have many ongoing projects using fastai for PyTorch, including a forthcoming new book, many new software features, and the majority of the content in the upcoming courses. This stack will remain the main focus of our teaching and development.

It is very early days for Swift for TensorFlow. We definitely don’t recommend anyone tries to switch all their deep learning projects over to Swift just yet! Right now, most things don’t work. Most plans haven’t even been started. For many, this is a good reason to skip the project entirely."