4 ms·

Plug for Mathematica, which after its installed you can do deep learning on in one or two lines, with GPU support on all three platforms with no setup. Very con

Plug for Mathematica, which after its installed you can do deep learning on in one or two lines, with GPU support on all three platforms with no setup. Very concise. Getting fairly competitive in features with other high level declarative frameworks as of 11.1 (which was just released today). Very nice visualizations thanks to being in Mathematica. The language is of course closed source, paid software. Many universities have site licenses, so there is a large built-in audience who can use it in courses etc 'for free', home licenses are comparable to photoshop or whatever. See http://reference.wolfram.com/language/guide/NeuralNetworks.html http://reference.wolfram.com/language/guide/NeuralNetworks.h..., also look at Examples > Applications under http://reference.wolfram.com/language/ref/NetTrain.html http://reference.wolfram.com/language/ref/NetTrain.html for some worked examples. Fun example of live visualization during training (very easy to do, will get even easier in future versions): https://twitter.com/taliesinb/status/839013689613254656 https://twitter.com/taliesinb/status/839013689613254656

aseipp 10y ago
Did y'all fix GTX 10x series compatibility with this release? Mathematica is some wonderful software, I admit -- but it was disappointing to try the NN examples and suddenly see nothing worked properly on my new GTX 1080 and I had to CPU train everything. :( I guess stuff like that's inevitable though so I'm not too upset. Guess the only way is to upgrade to 11.1 and find out, but since you're apparently involved -- might as well ask...
- taliesinb 10y ago
  Yup, it works. Sorry... GTX 10x required CUDA Toolkit 8.0 which was RC at the time we shipped 11.0.
jtraffic 10y ago
Two times in my life, I've gotten deeply excited about Mathematica. The first time I wanted to use it for economics homework as an undergraduate. (Don't worry, I did it on paper first.) The second time, I wanted to use it for machine learning, especially NLP. Mainly the knowledge base Mathematica hooks into is what drew me. The problem in the end is that the customizability of Mathematica ends right where things get interesting. If you want to show people cool little examples, Mathematica is clean and fast, but you can't build anything serious with it. And by "serious", I guess I mean something with few enough constraints to have an identity of its own, rather than being "a thing you can do with Mathematica." Another limitation is the data input. Someone needs to rethink it. I could be wrong. I actually want to be wrong, because of the simplicity and power of Mathematica in its scope. Programming languages/platforms are network goods. IMHO, Mathematica has tried to swim against this fact and has failed.
- taliesinb 10y ago
  > If you want to show people cool little examples, Mathematica is clean and fast, but you can't build anything serious with it. Mathematica, which is a serious project, is largely written in Mathematica. Wolfram|Alpha, another large project, is built in Mathematica. Outside the company, https://emeraldcloudlab.com/ https://emeraldcloudlab.com/ for example has built their platform on Mathematica. > And by "serious", I guess I mean something with few enough constraints to have an identity of its own, rather than being "a thing you can do with Mathematica." For research, a "thing you can do with Mathematica" is often what you want. But other than that you can put things you build in the cloud via APIFunctions (similar to AWS Lambda functions), or call out to them via wolframscript, or talk to kernels directly via MathLink or LibraryLink, or over sockets via ChannelListen. > Another limitation is the data input. Someone needs to rethink it seriously. That's vague, but I imagine you mean importers. Certain built-in importers aren't as good as they should be, like CSV and XLS are memory hogs and die on relatively small amounts of data (at least they used to, I haven't checked recently). The HDF5 importer is now pretty good, and for large datasets it's a good choice for scientific computing anyway. > Programming languages/platforms are network goods. IMHO, Mathematica has tried to swim against this fact and has failed. No arguments there. I think it would be great if we could open source at least parts of it, because no doubt new life would be breathed into cobwebby parts of the codebase and various pet peeves fixed. But Mathematica still dominates the computer algebra space despite being closed source, and probably will continue to do so for a while.
  - jtraffic 10y ago
    Good points. I will admit that what I said: "you can't build anything serious with it" is too extreme. I'm not sure how to count Mathematica and Wolfram|Alpha, though. Still, Emerald Cloud Lab clearly gets credit.
  - Nullabillity 10y ago
    > For research, a "thing you can do with Mathematica" is often what you want. But other than that you can put things you build in the cloud via APIFunctions (similar to AWS Lambda functions), or call out to them via wolframscript, or talk to kernels directly via MathLink or LibraryLink, or over sockets via ChannelListen. For research, closed source should be a dealbreaker.

aseipp 10y ago

Did y'all fix GTX 10x series compatibility with this release? Mathematica is some wonderful software, I admit -- but it was disappointing to try the NN examples and suddenly see nothing worked properly on my new GTX 1080 and I had to CPU train everything. :( I guess stuff like that's inevitable though so I'm not too upset. Guess the only way is to upgrade to 11.1 and find out, but since you're apparently involved -- might as well ask...

taliesinb 10y ago
Yup, it works. Sorry... GTX 10x required CUDA Toolkit 8.0 which was RC at the time we shipped 11.0.

jtraffic 10y ago

Two times in my life, I've gotten deeply excited about Mathematica. The first time I wanted to use it for economics homework as an undergraduate. (Don't worry, I did it on paper first.) The second time, I wanted to use it for machine learning, especially NLP. Mainly the knowledge base Mathematica hooks into is what drew me. The problem in the end is that the customizability of Mathematica ends right where things get interesting. If you want to show people cool little examples, Mathematica is clean and fast, but you can't build anything serious with it. And by "serious", I guess I mean something with few enough constraints to have an identity of its own, rather than being "a thing you can do with Mathematica." Another limitation is the data input. Someone needs to rethink it. I could be wrong. I actually want to be wrong, because of the simplicity and power of Mathematica in its scope. Programming languages/platforms are network goods. IMHO, Mathematica has tried to swim against this fact and has failed.

taliesinb 10y ago
> If you want to show people cool little examples, Mathematica is clean and fast, but you can't build anything serious with it. Mathematica, which is a serious project, is largely written in Mathematica. Wolfram|Alpha, another large project, is built in Mathematica. Outside the company, https://emeraldcloudlab.com/ https://emeraldcloudlab.com/ for example has built their platform on Mathematica. > And by "serious", I guess I mean something with few enough constraints to have an identity of its own, rather than being "a thing you can do with Mathematica." For research, a "thing you can do with Mathematica" is often what you want. But other than that you can put things you build in the cloud via APIFunctions (similar to AWS Lambda functions), or call out to them via wolframscript, or talk to kernels directly via MathLink or LibraryLink, or over sockets via ChannelListen. > Another limitation is the data input. Someone needs to rethink it seriously. That's vague, but I imagine you mean importers. Certain built-in importers aren't as good as they should be, like CSV and XLS are memory hogs and die on relatively small amounts of data (at least they used to, I haven't checked recently). The HDF5 importer is now pretty good, and for large datasets it's a good choice for scientific computing anyway. > Programming languages/platforms are network goods. IMHO, Mathematica has tried to swim against this fact and has failed. No arguments there. I think it would be great if we could open source at least parts of it, because no doubt new life would be breathed into cobwebby parts of the codebase and various pet peeves fixed. But Mathematica still dominates the computer algebra space despite being closed source, and probably will continue to do so for a while.
- jtraffic 10y ago
  Good points. I will admit that what I said: "you can't build anything serious with it" is too extreme. I'm not sure how to count Mathematica and Wolfram|Alpha, though. Still, Emerald Cloud Lab clearly gets credit.
- Nullabillity 10y ago
  > For research, a "thing you can do with Mathematica" is often what you want. But other than that you can put things you build in the cloud via APIFunctions (similar to AWS Lambda functions), or call out to them via wolframscript, or talk to kernels directly via MathLink or LibraryLink, or over sockets via ChannelListen. For research, closed source should be a dealbreaker.