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Andrew Ng updates his Machine Learning course

deeplearning.ai

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Re: Andrew Ng updates his Machine Learning course

#111

Post by BeetleB »

londons_explore wrote: post #41
BeetleB wrote: post #14

Earlier quoted context omitted.

The programming assignments in the original course were mostly useless. They provided you with a template with 90% of the problem solved, and you just had to enter an equation to solve the problem.

But you also had to understand the rest of the code in the template. And reading code tends to be a quicker way to learn roughly how something works than writing it from scratch.

> But you also had to understand the rest of the code in the template.

Not really. They had lots of comments that explained what the code did. You didn't need to read most of the code.

My point is that compared to real university courses, the HW in this course would be labeled as "trivial". Writing those few lines of code was no more instructive than an in class paper test. It's more comparable to answering simple questions than building anything.

I don't think I had to debug even once in that course. It was that easy.

Re: Andrew Ng updates his Machine Learning course

#112

Post by samstave »

UmbertoNoEco wrote: post #22
smnrchrds wrote: post #8

Earlier quoted context omitted.

What are the others? Any recommendations?

Depends, how much linear algebra, probability and python do you know?

What if one knows zilch, like my teenager... What might be best to start the path?

Re: Andrew Ng updates his Machine Learning course

#113

Post by UmbertoNoEco »

samstave wrote: post #112
UmbertoNoEco wrote: post #22

Earlier quoted context omitted.

Depends, how much linear algebra, probability and python do you know?

What if one knows zilch, like my teenager... What might be best to start the path?

OK, since it is for a teenager I would assume just basic computer competency (how to install programs and stuff like that) but nothing else, so apologies if some of these things are pretty obvious/basic..

I would (assuming zilch knowledge and tools).

- Install Python. https://www.python.org/downloads/

- Install VSC https://code.visualstudio.com/

- Install the python extension for VSC https://marketplace.visualstudio.com/items?itemName=ms-pytho...

- learn a little bit of python. This is a good resource, but there are several more, even the official documentation is very good

http://openbookproject.net/thinkcs/python/english3e/

- After some familiarity with python one option is this free book:

http://neuralnetworksanddeeplearning.com/

- Another, good (but paid) option is this book: https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-T...

Or a third option is indeed Andrew Ng's course.

Now, for any of those 3 options a little (or a lot) of guidance and patience will be needed so hopefully you or some friend/peer can help with that. Good luck!

Re: Andrew Ng updates his Machine Learning course

#114

Post by screye »

xwdv wrote: post #15

Although 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?

That'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.

Re: Andrew Ng updates his Machine Learning course

#115

Post by vasili111 »

vitorbaptistaa wrote: post #102
colordrops wrote: post #95

Earlier quoted context omitted.

If one is a seasoned software engineer, but has little experience in ML or deep learning, is this course still suitable?

Definitely. It starts from first principles, linear algebra, and goes from there. It's an amazing course.

So you need to know Linear algebra to understand? I knowing Algebra I enough to understad it?

Re: Andrew Ng updates his Machine Learning course

#116

Post by vasili111 »

NelsonMinar wrote: post #47
xwdv wrote: post #15

Although 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?

I 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 funct…

Is the knowing only Algebra I enough for this course?

Re: Andrew Ng updates his Machine Learning course

#117

Post by vasili111 »

aaaaaaaaaaab wrote: post #67
xwdv wrote: post #15

Although 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?

In 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.

Do 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.

Re: Andrew Ng updates his Machine Learning course

#118

Post by vasili111 »

saynay wrote: post #108
rg111 wrote: post #80

Earlier quoted context omitted.

Jeremy Howard came off as anti-intellectual to me. He is always like "oh math is nothing... you do not need math... math is not needed" and stuff like that. Other than that, fast.ai is a great resource, and Jeremy Howard is a great instructor. You will learn very practical tools and tricks, and a lot of recent research is demystified, but don't expect to achieve deep, general insights. Also, fast.ai is a very very li…

I wouldn't say Jeremy is anti-intellectual, but he does know that a lot of people get turned off from the AI field because they are afraid of the math, and a lot of other courses (used to?) start with the math. So he makes sure early and often to tell people that you don't need to understand the math that is happening deep under the hood in order to do productive, even state-of-the-art, research with AI.

What is the required math for starting Ng course?

Re: Andrew Ng updates his Machine Learning course

#119

Post by vasili111 »

_odey wrote: post #21
smnrchrds wrote: post #8

Earlier quoted context omitted.

What are the others? Any recommendations?

Not 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/

What is required math for starting Ng course?

Re: Andrew Ng updates his Machine Learning course

#120

Post by vasili111 »

kache_ wrote: post #105
colordrops wrote: post #95

Earlier quoted context omitted.

If one is a seasoned software engineer, but has little experience in ML or deep learning, is this course still suitable?

If you remember highschool AP math, you're good. Otherwise, check out ISLR for a faster intro, capped by your ability to read

Do you think ISLR is not outdated? I just looked at the date of publication and was wondering if it is still relevant.
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