Apache MXNet Deep Learning Framework
An Apache MXNet Deep Learning Framework is an multi-language open-source deep learning framework that ...
- Context:
- It can be accessed in code written in: C++, Python, Julia, Matlab, JavaScript, Go, R, Scala, Perl, and Wolfram Language.
- …
- Example(s):
- MXNet v1.1.0 ~(2018-02-15) [1]
- MXNet v1.0.0 ~(2017-12-07).
- MXNet v0.11.0 ~(2017-09-03).
- …
- Counter-Example(s):
- See: Distributed (Deep) Machine Learning, AWS EMR.
References
2018
- https://github.com/apache/incubator-mxnet
- QUOTE: Apache MXNet (incubating) is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scaling effectively to multiple GPUs and multiple machines.
MXNet is also more than a deep learning project. It is also a collection of blue prints and guidelines for building deep learning systems, and interesting insights of DL systems for hackers.
- QUOTE: Apache MXNet (incubating) is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scaling effectively to multiple GPUs and multiple machines.
2017
- (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/MXNet Retrieved:2017-7-4.
- MXNet is an open-source deep learning framework used to train, and deploy deep neural networks. It is scalable, allowing for fast model training, and supports a flexible programming model and multiple languages (C++, Python, Julia, Matlab, JavaScript, Go, R, Scala, Perl, Wolfram Language)
The MXNet library is portable and can scale to multiple GPUs and multiple machines. MXNet is supported by major Public Cloud providers including Azure and AWS. Amazon has chosen MXNet as its deep learning framework of choice at AWS. Currently, MXNet is supported by Intel, Dato, Baidu, Microsoft, Wolfram Research, and research institutions such as Carnegie Mellon, MIT, the University of Washington, and the Hong Kong University of Science and Technology.
- MXNet is an open-source deep learning framework used to train, and deploy deep neural networks. It is scalable, allowing for fast model training, and supports a flexible programming model and multiple languages (C++, Python, Julia, Matlab, JavaScript, Go, R, Scala, Perl, Wolfram Language)
2016
- https://www.quora.com/What-are-your-thoughts-on-TensorFlow/answer/Alex-Smola-1?share=67229161&srid=uuoZN
- QUOTE: … Compare this with MXNet, which, in my opinion, is the only realistic contender [to TensorFlow. It has an equally clean API, supports many different languages (Python, Julia, C++, JavaScript), has good legacy support (e.g. for Caffe code), and it is optimized for multi-machine and cheap hardware (try running Tensorflow on a GTX750 with 2GB RAM). This makes it much more accessible for projects outside Google.