The book linked at the top of the article is a great read[1]. Very easy to follow along if you want to do a similar thing yourself.
Building a neural network from scratch in Haskell
11–20 of 38 posts
Re: Building a neural network from scratch in Haskell
#12All these building NNs in haskell, ocaml or another language solving an extremely simple problem which is ok if you want to just have some fun. But if the proponents are really serious they would put out a detailed tutorial solving a complex task (e.g building a state-of-the-art language model) showing the ease / difficulty of the process, and how using a typed functional language helps in debugging the model - which…
Learning the basics has its place. People have to start somewhere. A tutorial for more complex, real world problems is a totally different thing. Both are interesting in their own ways.
If you have no background, why would you want to learn the basics in a language no one uses rather than the dominant language / framework of the specific domain? Seems to me an extra cognitive load to bear.
Re: Building a neural network from scratch in Haskell
#13All these building NNs in haskell, ocaml or another language solving an extremely simple problem which is ok if you want to just have some fun. But if the proponents are really serious they would put out a detailed tutorial solving a complex task (e.g building a state-of-the-art language model) showing the ease / difficulty of the process, and how using a typed functional language helps in debugging the model - which…
People have done this but with hasktorch. Which are haskell bindings to the pytorch C++ libraries. The static typing definitely helps when you want to ensure that the input/output shapes of a layer are consistent.
Re: Building a neural network from scratch in Haskell
#14Maybe it's just me, but this looks like a bunch of incomprehensible gibberish code. I'm sure I could understand it if I spent many hours pouring over it, but why would you ever do that? When written out in Python (or even in JS!), the whole thing is so much simpler looking and more closely resembles the underlying math. This is especially true if you use a package like Numpy. I know he said he didn't want to use any libraries, but if the underlying primitives in the problem are vectors/matrices, then it seems like you are reinventing the wheel in a very substandard way that doesn't aid in understanding in any way and results in something that isn't beautiful, isn't high performance, and is confusing for someone to read-- even if the person is familiar with the subject matter!
Re: Building a neural network from scratch in Haskell
#15Earlier quoted context omitted.
Learning the basics has its place. People have to start somewhere. A tutorial for more complex, real world problems is a totally different thing. Both are interesting in their own ways.
If you have no background, why would you want to learn the basics in a language no one uses rather than the dominant language / framework of the specific domain? Seems to me an extra cognitive load to bear.
Because it only takes one user to make language more popular. For example, Grammarly's first developer used Lisp as his main language, their linguistics is still written in a Lisp-family lang.
As a Haskell developer, I'd be more comfortable to read Haddock-generated documentation for types of symbols, unfortunately it doesn't have too many good quality libraries in the ML field yet.
Re: Building a neural network from scratch in Haskell
#16All these building NNs in haskell, ocaml or another language solving an extremely simple problem which is ok if you want to just have some fun. But if the proponents are really serious they would put out a detailed tutorial solving a complex task (e.g building a state-of-the-art language model) showing the ease / difficulty of the process, and how using a typed functional language helps in debugging the model - which…
People have done this but with hasktorch. Which are haskell bindings to the pytorch C++ libraries. The static typing definitely helps when you want to ensure that the input/output shapes of a layer are consistent.
Can you please point to such a tutorial? I am interested.
Re: Building a neural network from scratch in Haskell
#17Earlier quoted context omitted.
Learning the basics has its place. People have to start somewhere. A tutorial for more complex, real world problems is a totally different thing. Both are interesting in their own ways.
If you have no background, why would you want to learn the basics in a language no one uses rather than the dominant language / framework of the specific domain? Seems to me an extra cognitive load to bear.
I am learning the basics of neural nets using Haskell because it’s far easier for me to reason precisely and mathematically with Haskell than with a referentially opaque and imprecise language such as Python.
Re: Building a neural network from scratch in Haskell
#18Where is 8? I flipped the sample like 100+ times. Didn't encounter a single #8. I guess Haskell bytes back sometimes.
Re: Building a neural network from scratch in Haskell
#19Maybe it's just me, but this looks like a bunch of incomprehensible gibberish code. I'm sure I could understand it if I spent many hours pouring over it, but why would you ever do that? When written out in Python (or even in JS!), the whole thing is so much simpler looking and more closely resembles the underlying math. This is especially true if you use a package like Numpy. I know he said he didn't want to use any…
but if the underlying primitives in the problem are vectors/matrices, then it seems like you are reinventing the wheel in a very substandard way that doesn't aid in understanding in any way and results in something that isn't beautiful, isn't high performance, and is confusing for someone to read
You mean like...both of the languages you listed?
There's an obviously superior, faster, simpler language when working with vectors (APL), but people are obsessed with new languages.
If you really think it can be done in Python better than in Haskell, why not demo it in Python? You'll get internet points, and if you're right, you'll have something to show for it.
Re: Building a neural network from scratch in Haskell
#20Where is 8? I flipped the sample like 100+ times. Didn't encounter a single #8. I guess Haskell bytes back sometimes.
If this is a failing of the language, then at least blame the right one.