7 ms·

If anyone wants to delve into machine learning, one of the superb resources I have found is, Stanfords "Probability for computer scientists"(https://www.youtube

If anyone wants to delve into machine learning, one of the superb resources I have found is, Stanfords "Probability for computer scientists"(https://www.youtube.com/watch?v=2MuDZIAzBMY&list=PLoROMvodv4rOpr_A7B9SriE_iZmkanvUg https://www.youtube.com/watch?v=2MuDZIAzBMY&list=PLoROMvodv4...). It delves into theoretical underpinnings of probability theory and ML, IMO better than any other course I have seen. (Yeah, Andrew Ng is legendary, but his course demands some mathematical familarity with linear algebra topics) And of course, for deep learning, 3b1b is great for getting some visual introduction (https://www.youtube.com/watch?v=aircAruvnKk&list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi https://www.youtube.com/watch?v=aircAruvnKk&list=PLZHQObOWTQ...).

rottc0dd 2y ago
Caltech's learning from data was really good too, if someone is looking for theoretical understanding of ML topics. https://work.caltech.edu/telecourse https://work.caltech.edu/telecourse
- abhgh 2y ago
  I highly recommend the course you've mentioned (by Yaser Abu-Mostafa). In fact I still recommend it for picking up the basics; very good mix of math and intuition, Abu-Mostafa himself is a terrific teacher, and he is considerate and thoughtful in responding to questions at the end of his presentations. The last part is important if you're a beginner: it builds confidence in you that its probably ok to ask what you might consider a simple question - it still deserves a good answer. The series is a bit dated now in terms of what it covers, but still solid as a foundational course.
_ce5e 2y ago
Fully agree! 3blue1brown is who have single-handedly thought me a majority of what I've needed to know about it. I actually started building my own neural network framework last week in C++! It's a great way to delve into the details of how they work. It currently supports only dense MLP's, but does so quite well, and work is underway for convolutional layers and pooling layers on a separate branch. https://github.com/perkele1989/prkl-ann https://github.com/perkele1989/prkl-ann
randomtoast 2y ago
Apparently the word “delve” is the biggest indicator of the use of ChatGPT according to Paul Graham.
- djmips 2y ago
  So ChatGPT or Nigerians or me apparently... :`(
- wincy 2y ago
  I’d love to see an article delve into why that is.
  - treyd 2y ago
    Because it's common in Nigerian English, which is where they outsourced a lot of the RLHF conditioning work to.
    - Hugsun 2y ago
      Really!? Do you have a source for this? This would be really interesting if true.
      - cratermoon 2y ago
        https://www.theguardian.com/technology/2024/apr/16/techscape-ai-gadgest-humane-ai-pin-chatgpt https://www.theguardian.com/technology/2024/apr/16/techscape...
  - sva_ 2y ago
    https://pshapira.net/2024/03/31/delving-into-delve/ https://pshapira.net/2024/03/31/delving-into-delve/
- EGreg 2y ago
  Saying that kind of stuff is the biggest indicator of Paul Graham (pg) himself
- 2y ago
samstave 2y ago
[dead]
chamomeal 2y ago
I watched the 3b1b series on neural nets years ago, and it still accounts for 95% of my understanding of AI in general. I’m not an ML person, but still. That guy has a serious gift for explaining stuff. His video on the uncertainty principle explained stuff to me that my entire undergrad education failed to!
- nomel 2y ago
  https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_6700...
- eru 2y ago
  It helps that 3b1b doesn't start with a curriculum and then has to figure out how to teach it. Instead he can select topics to suit his style.
- salviati 2y ago
  > That guy has a serious gift for explaining stuff I'd like to challenge this idea. I don't believe he's more gifted than other people. I strongly believe that the point is he spent a lot of time and effort to get better at explaining stuff. He contemplated feedback and improved his explanations throughout the years. His videos are excellent because he poured himself into making them excellent, not because he has a gift. In my experience the professors who lack this ability do so because they don't put enough effort into it, not because they were born without it.
  - idiotsecant 2y ago
    To be very good at something it is necessary, but not sufficient, to have a talent for it. The other 85% is hard work. You aren't going to pull just anyone off the street and have the same level of instruction, no matter how motivated they are.
  - jmull 2y ago
    You're probably reading too much into previous poster's choice of the word "gift". Most likely it is a slightly misused idiom rather than intending to convey that the teaching ability was obtained without effort.
bogeholm 2y ago
Looks nice - are there written versions?
- rottc0dd 2y ago
  There is a course reader for CS109 [1]. You can download pdf version of this. There is also book[2] for excellent caltech course[3]. [1] https://chrispiech.github.io/probabilityForComputerScientists/en/ https://chrispiech.github.io/probabilityForComputerScientist... [2] https://www.amazon.com/Learning-Data-Yaser-S-Abu-Mostafa/dp/1600490069 https://www.amazon.com/Learning-Data-Yaser-S-Abu-Mostafa/dp/... [3] https://work.caltech.edu/telecourse https://work.caltech.edu/telecourse
  - bogeholm 2y ago
    Thanks!
vcdimension 2y ago
and if anyone is interested in delving more deeply into the statistical concepts & results referenced in the paper of this post (e.g. VC-dimension, PAC-learning, etc), I can recommend this book: https://amzn.eu/d/7Zwe6jw https://amzn.eu/d/7Zwe6jw
andirk 2y ago
Just watched the whole thing. Thanks! I can't get in to my Masters CS: AI program at UC Berkeley because I'm dumb, but seeing this 1st day of a Probability class kinda felt like I was beginning that program haha. I will add a great find for starting one's AI journey https://www.youtube.com/watch?v=_xIwjmCH6D4 https://www.youtube.com/watch?v=_xIwjmCH6D4 . Kind of needs one to know intermediate CS since 1st step is "learn Python".
Vaslo 2y ago
Great recommendations
cake-rusk 2y ago
Yeah I took CS109 (through SCPD), it was a blast. But it took some serious time commitment.
rottc0dd 2y ago
From, a comment I posted elsewhere for written versions. There is a course reader for CS109 [1]. You can download pdf version of this. There is also book[2] for excellent caltech course[3]. [1] https://chrispiech.github.io/probabilityForComputerScientist https://chrispiech.github.io/probabilityForComputerScientist... [2] https://www.amazon.com/Learning-Data-Yaser-S-Abu-Mostafa/dp/ https://www.amazon.com/Learning-Data-Yaser-S-Abu-Mostafa/dp/... [3] https://work.caltech.edu/telecourse https://work.caltech.edu/telecourse
- deleted 2y ago
  [deleted]
- stevesimmons 2y ago
  Your first two links don't work
  - gnabgib 2y ago
    That's because they posted them somewhere else (easy mistake to make.. HN doesn't show you the full link in a comment, so copy/paste just copies the ellipsis) https://chrispiech.github.io/probabilityForComputerScientists/en/ https://chrispiech.github.io/probabilityForComputerScientist... https://www.amazon.com/Learning-Data-Yaser-S-Abu-Mostafa/dp/1600490069 https://www.amazon.com/Learning-Data-Yaser-S-Abu-Mostafa/dp/...
    - rottc0dd 2y ago
      Thanks. Sorry for the oversight.

rottc0dd 2y ago

Caltech's learning from data was really good too, if someone is looking for theoretical understanding of ML topics. https://work.caltech.edu/telecourse https://work.caltech.edu/telecourse

abhgh 2y ago
I highly recommend the course you've mentioned (by Yaser Abu-Mostafa). In fact I still recommend it for picking up the basics; very good mix of math and intuition, Abu-Mostafa himself is a terrific teacher, and he is considerate and thoughtful in responding to questions at the end of his presentations. The last part is important if you're a beginner: it builds confidence in you that its probably ok to ask what you might consider a simple question - it still deserves a good answer. The series is a bit dated now in terms of what it covers, but still solid as a foundational course.

_ce5e 2y ago

Fully agree! 3blue1brown is who have single-handedly thought me a majority of what I've needed to know about it. I actually started building my own neural network framework last week in C++! It's a great way to delve into the details of how they work. It currently supports only dense MLP's, but does so quite well, and work is underway for convolutional layers and pooling layers on a separate branch. https://github.com/perkele1989/prkl-ann https://github.com/perkele1989/prkl-ann

randomtoast 2y ago

Apparently the word “delve” is the biggest indicator of the use of ChatGPT according to Paul Graham.

djmips 2y ago
So ChatGPT or Nigerians or me apparently... :`(
wincy 2y ago
I’d love to see an article delve into why that is.
- treyd 2y ago
  Because it's common in Nigerian English, which is where they outsourced a lot of the RLHF conditioning work to.
  - Hugsun 2y ago
    Really!? Do you have a source for this? This would be really interesting if true.
    - cratermoon 2y ago
      https://www.theguardian.com/technology/2024/apr/16/techscape-ai-gadgest-humane-ai-pin-chatgpt https://www.theguardian.com/technology/2024/apr/16/techscape...
- sva_ 2y ago
  https://pshapira.net/2024/03/31/delving-into-delve/ https://pshapira.net/2024/03/31/delving-into-delve/
EGreg 2y ago
Saying that kind of stuff is the biggest indicator of Paul Graham (pg) himself
2y ago

samstave 2y ago

[dead]

chamomeal 2y ago

I watched the 3b1b series on neural nets years ago, and it still accounts for 95% of my understanding of AI in general. I’m not an ML person, but still. That guy has a serious gift for explaining stuff. His video on the uncertainty principle explained stuff to me that my entire undergrad education failed to!

nomel 2y ago
https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_6700...
eru 2y ago
It helps that 3b1b doesn't start with a curriculum and then has to figure out how to teach it. Instead he can select topics to suit his style.
salviati 2y ago
> That guy has a serious gift for explaining stuff I'd like to challenge this idea. I don't believe he's more gifted than other people. I strongly believe that the point is he spent a lot of time and effort to get better at explaining stuff. He contemplated feedback and improved his explanations throughout the years. His videos are excellent because he poured himself into making them excellent, not because he has a gift. In my experience the professors who lack this ability do so because they don't put enough effort into it, not because they were born without it.
- idiotsecant 2y ago
  To be very good at something it is necessary, but not sufficient, to have a talent for it. The other 85% is hard work. You aren't going to pull just anyone off the street and have the same level of instruction, no matter how motivated they are.
- jmull 2y ago
  You're probably reading too much into previous poster's choice of the word "gift". Most likely it is a slightly misused idiom rather than intending to convey that the teaching ability was obtained without effort.

bogeholm 2y ago

Looks nice - are there written versions?

rottc0dd 2y ago
There is a course reader for CS109 [1]. You can download pdf version of this. There is also book[2] for excellent caltech course[3]. [1] https://chrispiech.github.io/probabilityForComputerScientists/en/ https://chrispiech.github.io/probabilityForComputerScientist... [2] https://www.amazon.com/Learning-Data-Yaser-S-Abu-Mostafa/dp/1600490069 https://www.amazon.com/Learning-Data-Yaser-S-Abu-Mostafa/dp/... [3] https://work.caltech.edu/telecourse https://work.caltech.edu/telecourse
- bogeholm 2y ago
  Thanks!

vcdimension 2y ago

and if anyone is interested in delving more deeply into the statistical concepts & results referenced in the paper of this post (e.g. VC-dimension, PAC-learning, etc), I can recommend this book: https://amzn.eu/d/7Zwe6jw https://amzn.eu/d/7Zwe6jw

andirk 2y ago

Just watched the whole thing. Thanks! I can't get in to my Masters CS: AI program at UC Berkeley because I'm dumb, but seeing this 1st day of a Probability class kinda felt like I was beginning that program haha. I will add a great find for starting one's AI journey https://www.youtube.com/watch?v=_xIwjmCH6D4 https://www.youtube.com/watch?v=_xIwjmCH6D4 . Kind of needs one to know intermediate CS since 1st step is "learn Python".

Vaslo 2y ago

Great recommendations

cake-rusk 2y ago

Yeah I took CS109 (through SCPD), it was a blast. But it took some serious time commitment.

rottc0dd 2y ago

From, a comment I posted elsewhere for written versions. There is a course reader for CS109 [1]. You can download pdf version of this. There is also book[2] for excellent caltech course[3]. [1] https://chrispiech.github.io/probabilityForComputerScientist https://chrispiech.github.io/probabilityForComputerScientist... [2] https://www.amazon.com/Learning-Data-Yaser-S-Abu-Mostafa/dp/ https://www.amazon.com/Learning-Data-Yaser-S-Abu-Mostafa/dp/... [3] https://work.caltech.edu/telecourse https://work.caltech.edu/telecourse

deleted 2y ago
[deleted]
stevesimmons 2y ago
Your first two links don't work
- gnabgib 2y ago
  That's because they posted them somewhere else (easy mistake to make.. HN doesn't show you the full link in a comment, so copy/paste just copies the ellipsis) https://chrispiech.github.io/probabilityForComputerScientists/en/ https://chrispiech.github.io/probabilityForComputerScientist... https://www.amazon.com/Learning-Data-Yaser-S-Abu-Mostafa/dp/1600490069 https://www.amazon.com/Learning-Data-Yaser-S-Abu-Mostafa/dp/...
  - rottc0dd 2y ago
    Thanks. Sorry for the oversight.