Also, I think pylearn2 and theano-nets only support CUDA cards (Nvidia),
since Teahno only supports CUDA or CPU to my knowledge. There is some
discussion of supporting an OpenCL backend (
https://groups.google.com/forum/#!msg/theano-dev/NhRUhWA6xzo/lYrIIOlw4D8J),
but I don't know whether that work was ever completed. Maybe someone else
has a better knowledge of this.
On Mon, Apr 7, 2014 at 2:39 PM, Kyle Kastner <[email protected]> wrote:
> You can also use the python interface to pylearn2, rather than the yaml.
> If you are interested in examples of the python interface for pylearn2, I
> have some examples (I greatly prefer the python interface, but to each
> their own):
>
>
> https://github.com/kastnerkyle/pylearn2-practice/blob/master/cifar10_train.pyshows
> how to build a network and test using a pylearn2 builtin dataset
>
>
> https://github.com/kastnerkyle/kaggle-dogs-vs-cats/blob/master/kaggle_train.py
> This shows how to use scikit-learn's train-test split to create training
> and testing classes for new datasets in pylearn2 format. x and y are both
> 2D. Rows are samples, columns are features for x. y generally needs to be a
> "one hot" label matrix for classification, but will be a regression target
> for RMSE/regression tasks.
>
> In general, it is pretty easy to wrap your data into a pylearn2 compatible
> format, though doing "raw" input for convolutional nets can be tricky. I
> have an example of reading pngs from Kaggle's CIFAR10 competition into
> pylearn2 and using a convnet here:
> https://github.com/kastnerkyle/kaggle-cifar10
>
> All that being said, theano-nets *can* be easier to start with for those
> who are new to neural networks, as it is a little less roll-your-own.
>
> I have had success using both.
>
> Kyle
>
>
> On Mon, Apr 7, 2014 at 11:48 AM, Ralf Gunter <[email protected]> wrote:
>
>> Two libraries[1,2] come to mind that can additionally support
>> accelerators through opencl. Just take note that it can take a bit to
>> familiarize yourself with pylearn2, especially because they seem
>> adamant in doing everything through yaml scripts.
>>
>> [1] -- https://github.com/lmjohns3/theano-nets (see e.g.
>> examples/xor-classfier.py)
>> [2] -- http://deeplearning.net/software/pylearn2
>>
>> 2014-04-07 11:18 GMT-05:00 Yuxiang Wang <[email protected]>:
>> > Dear all,
>> >
>> > I am not entirely sure whether this is the best place to post this,
>> > and please do excuse me if this is not the perfect list for this
>> > question.
>> >
>> > Is there any python packages for neural networks for regression
>> > (instead of classification)?
>> >
>> > Any help would be appreciated. Thanks!
>> >
>> > -Shawn
>> >
>> >
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