It's a bad idea to learn deep learning without learning the math.
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Open source deep learning models that programmers can download and run first try
31–40 of 44 posts
Re: Open source deep learning models that programmers can download and run first try
#32Earlier quoted context omitted.
I disagree, now prove your point.
Question: What is DL without the math? Network design? Stacking nodes in a graph in arbitrary ways? The days of handcracted design are numbered anyways, so learning DL without the math is not a good long term investment.
Disagree. We will build abstraction layers on top of the best tools as we always have. You don't need to know assembly to be a programmer any more.
Re: Open source deep learning models that programmers can download and run first try
#33It's a bad idea to learn deep learning without learning the math.
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Re: Open source deep learning models that programmers can download and run first try
#34It's a bad idea to learn deep learning without learning the math.
I'm almost completing my phd in math, and as much as it pains me to say this, I think a great amount of deep learning can be accessible without "the math". And as tempting as it is to tell everyone to pay their mathematical dues by carrying the proverbial buckets of water up the steps, you can get by very well in the field with only the very basic basics of mathematical knowledge.
This is how i'd describe it. Deep learning is a set of tinker toys. Lego blocks if you will that you can sculpt with data into some very interesting models. Its an art, where the brushstrokes are matrices. Place an attention module here, and a convolution net there. And throw in a tensor with a softmax, and viola.
Now I love math. and part of me really wants to see deep learning become a mathematical discipline. Deep in the backwaters there are parts of deep learning involve some math (think variational inference, bayesian models, etc). And I do want deep learning to be about condition numbers and combinatorics. But if you want to be perfectly honest with a newbie in the field, if you want to get your feet wet in deep learning, don't waste 3 months on a class on advanced optimization or measure theory or probability. Just dive in
Re: Open source deep learning models that programmers can download and run first try
#35Gosh I wish this existed for Python.
Re: Open source deep learning models that programmers can download and run first try
#36It's a bad idea to learn deep learning without learning the math.
I'm almost completing my phd in math, and as much as it pains me to say this, I think a great amount of deep learning can be accessible without "the math". And as tempting as it is to tell everyone to pay their mathematical dues by carrying the proverbial buckets of water up the steps, you can get by very well in the field with only the very basic basics of mathematical knowledge. This is how i'd describe it. Deep le…
I pretty much agree with you. I have a bachelor's degree in pure mathematics from a top 15 university -- I even published research as an undergraduate. Deep learning strikes me as an experimental science and even a subset of ordinary programming more than it does a subset of mathematics or statistics or statistical learning. I've read the entirety of the Deep Learning book by Goodfellow et. al. It's a fantastic book, but I was shocked at the lack of robust theory and the relative simplicity of the math. Even an introductory analysis textbook like Rudin is considerably harder, and Rudin is regularly tackled by undergraduates at any highly ranked university.
The only reason to fret about this in my opinion is if you're a PhD machine learning engineer who doesn't want the field to open up to non-PhDs. I think data scientists are used to being able to say, "hey, if you don't have a PhD, you really can't do or understand what I do" -- deep learning represents potentially a huge culture shock to that attitude. But even the Google Brain research team has some non-PhDs now.
I do think deep learning practitioners should learn the math. I just don't think there's actually that much math to learn. Certainly, if you read through the TensorFlow MNIST tutorial and you have no idea what cross-entropy is and you don't understand what the softmax layer is for, you need to go back to the basics. But these are concepts that anyone with any reasonable engineering degree can pick up relatively quickly.
As an example, I submit the five articles on Distill, a new online machine learning journal:
Notice that only the first has any real math, and even there the math is just not very advanced -- it's undergraduate-level.
Re: Open source deep learning models that programmers can download and run first try
#37Earlier quoted context omitted.
I'm almost completing my phd in math, and as much as it pains me to say this, I think a great amount of deep learning can be accessible without "the math". And as tempting as it is to tell everyone to pay their mathematical dues by carrying the proverbial buckets of water up the steps, you can get by very well in the field with only the very basic basics of mathematical knowledge. This is how i'd describe it. Deep le…
I pretty much agree with you. I have a bachelor's degree in pure mathematics from a top 15 university -- I even published research as an undergraduate. Deep learning strikes me as an experimental science and even a subset of ordinary programming more than it does a subset of mathematics or statistics or statistical learning. I've read the entirety of the Deep Learning book by Goodfellow et. al. It's a fantastic book,…
hey, I authored the first article :D
Re: Open source deep learning models that programmers can download and run first try
#38It's a bad idea to learn deep learning without learning the math.
Then again, you probably learned how to sort a list in Python, before you heard about TimSort. Going the other way around is commendable, but not necessary.
If a student wants to learn how to play the guitar, you show them 3 chords so they can play Bob Marley or Oasis.
You don't require them to first study consonance, dissonance, rhythm, melody, timbre, dynamics, articulation, texture, form, expression, notation, song writing, Schenkerian analysis, harmonic identity, semiotics, and musical set theory.
Someone who can play the guitar with a passion, can be taught to learn musical notation. The other way around is not guaranteed.
Your suggestion is not necessarily bad: It's good to learn the maths about the Wasserstein metric if you are using GAN's. But for effective teaching your suggestion is archaic, and part of the mindset that makes student's eyes glaze over when being taught mathematics. Can you point to a success story of a student to neural network researcher that did not start with a practical application?
Re: Open source deep learning models that programmers can download and run first try
#39There isnt really any math to deep learning other than the concept of a derivative which is taught in high school calculus. The reason deep learning papers seem mathy is people take network architectures and various elementary operations on them and try to express them symbolically in latex using summations and indexing-hell. For example the easy concept of "updating all the neurons in one layer based on the neurons…
If we could calculate the perfect model architecture for all unseen data, without relying on evaluation/experimentation/heuristics, then we'd have effectively solved the halting problem.
Mathematically, closest to that would be Hilbert's program.
Though neural nets can paint like Van Gogh nowadays, asking them to come up with Hilbert's program may be a bit too much of an ask. Yet I would not deeply mind if researchers would revisit papers like http://www.ics.uci.edu/~rickl/publications/1996-icml.pdf "On the Learnability of the Uncomputable".
Re: Open source deep learning models that programmers can download and run first try
#40Earlier quoted context omitted.
I'm almost completing my phd in math, and as much as it pains me to say this, I think a great amount of deep learning can be accessible without "the math". And as tempting as it is to tell everyone to pay their mathematical dues by carrying the proverbial buckets of water up the steps, you can get by very well in the field with only the very basic basics of mathematical knowledge. This is how i'd describe it. Deep le…
I pretty much agree with you. I have a bachelor's degree in pure mathematics from a top 15 university -- I even published research as an undergraduate. Deep learning strikes me as an experimental science and even a subset of ordinary programming more than it does a subset of mathematics or statistics or statistical learning. I've read the entirety of the Deep Learning book by Goodfellow et. al. It's a fantastic book,…
Do you have any recommendations for books to get into deep learning? I want some theory and math, but not too much because I do not have that much mathamitical background. I have only gone through calculus 2. (I will be taking calc 3 this coming semester). I am a computer science major.
I have dabbled in writing a super simple neural network to solve the MNIST. Using an example written in python and porting it to go, so that I couldn't copy and paste. I had to see what each step did. It very rapidly went to about 30% accuracy and stuck there. So I know I did something wrong. But I abandoned it after not being able to figure out what.