I wish someone would come up with a tutorial for ML for the mathematically challenged. Something more practical and less theoretical.
Andrew Ng has an excellent ML course on coursera [1] that is very light on math.
MNIST for ML Beginners: The Bayesian Way
11–20 of 37 posts
Re: MNIST for ML Beginners: The Bayesian Way
#12I wish people would stop using Raleway or implement a fix. This is what I see:
Re: MNIST for ML Beginners: The Bayesian Way
#13Earlier quoted context omitted.
I get it, and I've actually used the same metaphor just a couple days ago. What I mean though, is that the maths are OK, and although the heavy notation goes over my head (as I'm not academic), I understand the ideas. But I'm lacking some practical examples of how this is put to use. I understand how neural networks work for example, but I do not understand the maths behind how they work. There was (is?) a site calle…
Honestly, the best thing you can do is try to implement your own shitty neural net with only Python + Numpy, from scratch, with only a basic understanding of the math. It will make most of the math very concrete very fast.
Good idea! I'll give it a go
Re: MNIST for ML Beginners: The Bayesian Way
#14I wish people would stop using Raleway or implement a fix. This is what I see: http://imgur.com/a/locAq
Can you elaborate what the issue is? The site looks nothing like that to me. I see much more contrast. http://imgur.com/g49XOip
I ask because I like and plan to use Raleway on my blog and would hate to have readability issues.
Re: MNIST for ML Beginners: The Bayesian Way
#15Earlier quoted context omitted.
I get it, and I've actually used the same metaphor just a couple days ago. What I mean though, is that the maths are OK, and although the heavy notation goes over my head (as I'm not academic), I understand the ideas. But I'm lacking some practical examples of how this is put to use. I understand how neural networks work for example, but I do not understand the maths behind how they work. There was (is?) a site calle…
Honestly, the best thing you can do is try to implement your own shitty neural net with only Python + Numpy, from scratch, with only a basic understanding of the math. It will make most of the math very concrete very fast.
Naive question : is this strategy equally effective for all ML models?
Re: MNIST for ML Beginners: The Bayesian Way
#16I wish someone would come up with a tutorial for ML for the mathematically challenged. Something more practical and less theoretical.
That's been done: http://course.fast.ai Can't recommend this enough.
Halfway through, it's really good. Also much more understandable since he shows you toy examples in Excel and gives you the workbooks to play with.
Re: MNIST for ML Beginners: The Bayesian Way
#17Earlier quoted context omitted.
Honestly, the best thing you can do is try to implement your own shitty neural net with only Python + Numpy, from scratch, with only a basic understanding of the math. It will make most of the math very concrete very fast.
Naive question : is this strategy equally effective for all ML models?
This strategy is equally effective for most things in life.
Re: MNIST for ML Beginners: The Bayesian Way
#18I wish someone would come up with a tutorial for ML for the mathematically challenged. Something more practical and less theoretical.
I'm currently following Andrew Ng's machine learning course on Coursera. I was initially a bit concerned because it's been a long time since I've had to do any serious math, but I think he strikes a really nice balance between enough math to understand what the algorithms do, and not so much that you get scared away by too much depth or too many concepts at once. The practical assignments also have this nice balance. I highly recommend it -- if you can remember the basics of algebra and calculus (I mean really the basics, like that if you differentiate the equation of a straight line then it gives you the tangent of the line), then you will probably not get too lost.
The programming assignments also give you that nice practical experience: you get training sets to code and run ML algorithms against, using a language (Octave) that has a nice mix of low/high level-ness.
I strongly recommend it.
Re: MNIST for ML Beginners: The Bayesian Way
#19Earlier quoted context omitted.
Naive question : is this strategy equally effective for all ML models?
This strategy is equally effective for most things in life.
> This strategy is equally effective for most things in life.
Not if we understand 'effective' to also mean 'cost & time effective'
You'd learn a lot by building a nuclear reactor from first principles, but it's not the most effective way to develop an intuition about how one operates.
Re: MNIST for ML Beginners: The Bayesian Way
#20I wish people would stop using Raleway or implement a fix. This is what I see: http://imgur.com/a/locAq
Can you elaborate what the issue is? The site looks nothing like that to me. I see much more contrast. http://imgur.com/g49XOip I ask because I like and plan to use Raleway on my blog and would hate to have readability issues.
There is a known issue regarding Raleway due to aliasing in Chrome, see:
https://webmasters.stackexchange.com/questions/74672/renderi...
I hear claims it has been fixed, but I still see the issue in Chromium 58 on Linux.
Here's one bug which seems to have been tracking the issue with no resolution as of yet:
https://bugs.chromium.org/p/chromium/issues/detail?id=152304
You can see in the final comment from November of 2015 that the issue was, and from my experience still is, massively affecting Raleway:
https://bugs.chromium.org/p/chromium/issues/detail?id=152304...
EDIT: I just checked and this issue no longer affects me in Chrome 59 on Windows. Although I still have the issue on Linux.