Here is a little more detailed summary about Theano, which I wrote up on that thread:
Theano is a CPU and GPU compiler for mathematical expressions in Python. It combines the convenience of NumPy with the speed of optimized native machine language. For gradient-based machine learning algorithms (like training an MLP or convolutional net), Theano is from 1.6x to 7.5x faster than competitive alternatives (including those in C/C++, NumPy, SciPy, and Matlab) when compiled for the CPU and between 6.5x and 44x faster when compiled for the GPU. The SciPy 2010 paper is a good introduction: http://www.iro.umontreal.ca/~lisa/pointeurs/theano_scipy2010...
We discussed Python ML packages on MetaOptimize: http://metaoptimize.com/qa/questions/3053/python-machine-lea...
Here is a little more detailed summary about Theano, which I wrote up on that thread:
Theano is a CPU and GPU compiler for mathematical expressions in Python. It combines the convenience of NumPy with the speed of optimized native machine language. For gradient-based machine learning algorithms (like training an MLP or convolutional net), Theano is from 1.6x to 7.5x faster than competitive alternatives (including those in C/C++, NumPy, SciPy, and Matlab) when compiled for the CPU and between 6.5x and 44x faster when compiled for the GPU. The SciPy 2010 paper is a good introduction: http://www.iro.umontreal.ca/~lisa/pointeurs/theano_scipy2010...