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Caffe vs Theano/Pylearn2
Transcript
Sources
- Deeplearning4j.net (n.d.) Retrieved 28 Feb 16 from http://deeplearning4j.org/compare-dl4j-torch7-pylearn.html
- Mayank, Muktabh (1 Apr 15) Retrieved 28 Feb 16 from https://www.quora.com/Which-is-the-best-deep-learning-framework-Theano-Torch7-or-Caffe
- Nicholson, Chris(25 Feb 15) Retrieved 28 Feb 16 from https://www.quora.com/How-do-deeplearning4j-and-Caffe-compare
- Unknown (n.d.) Retrieved 28 Feb 16 from http://deeplearning.net/software/theano/introduction.html#introduction
Caffe
- Developed by the Berkeley Vision and Learning Center.
- Supports CuDNN
- Supports Conv Nets
- Written in C/C++
- Caffe specializes in machine vision (Nicholson, 25 Feb 15.) and per deeplearning4j.org, Caffee is not intended for other deep-learning applications such as text, sound or time series data (n.d).
- Per Mayank, Caffe is basically PyLearn2-like (1 Apr 2015)
Theano/Pylearn2
- Theano was written at the LISA lab (Universtiy of Montreal) to support rapid development of efficient machine learning algorithms.
- Supports CuDNN
- Supports Conv Nets
- Written in Python
- Pylearn2 is a normal (non-distributed) framework that includes everything necessary to conduct experiments with multilayer Perceptrons, restricted Boltzmann machines, Stacked Denoising Autoencoders and Convolutional nets (Deeplearning4j, n.d.)
Tutorial:
- http://outlace.com/Beginner-Tutorial-Theano/
Short Answer
This is similar to comparing a Ford to a Chevy. Both Caffe and Theano/Pylearn2 are Machine Learning libraries utilizing backpropogation, gradient descent, biases, weights and hidden layers. The differences lie in development and execution.
Caffe vs Theano/Pylearn2
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