On Tuesday, November 10, 2015 at 9:57:21 PM UTC-8, Valentin Churavy wrote:
>
> It fits in the same niche that Mocha.jl and MXNet.jl are filling right 
> now. MXNet is a ML library that shares many of the same design ideas of 
> TensorFlow and has great Julia support https://github.com/dmlc/MXNet.jl
>

MXNet and TensorFlow look like very similar frameworks. Both use symbolic 
computation which means they both create a DAG that can be manipulated and 
optimized for the underlying hardware (cpu or gpu). It would be interesting 
to see some comparisons between the two. I've read on another forum that 
MXNet is probably faster than TensorFlow at this point, but nobody has done 
any benchmarks yet (I'd try, but I don't have a GPU available at this 
point).

This DAG optimization step is pretty much a compiler in itself, I wonder 
how many similarities there are to ParallelAccelerator.jl? One could 
imagine borrowing some of ideas from it and taking advantage of Julia's 
macro features (which Python and C++ lack) to create a native Julia ML 
toolkit that could also have very high performance... problem is, there are 
so many ML toolkits coming out now that things are already getting pretty 
fragmented in the space.


>
> On Wednesday, 11 November 2015 01:04:00 UTC+9, Randy Zwitch wrote:
>>
>> For me, the bigger question is how does TensorFlow fit in/fill in gaps in 
>> currently available Julia libraries? I'm not saying that someone who is 
>> sufficiently interested shouldn't wrap the library, but it'd be great to 
>> identify what major gaps remain in ML for Julia and figure out if 
>> TensorFlow is the right way to proceed. 
>>
>> We're certainly nowhere near the R duplication problem yet, but certainly 
>> we're already repeating ourselves in many areas.
>>
>> On Monday, November 9, 2015 at 4:02:36 PM UTC-5, Phil Tomson wrote:
>>>
>>> Google has released it's deep learning library called TensorFlow as open 
>>> source code:
>>>
>>> https://github.com/tensorflow/tensorflow
>>>
>>> They include Python bindings, Any ideas about how easy/difficult it 
>>> would be to create Julia bindings?
>>>
>>> Phil
>>>
>>

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