Theano
mxnet
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Theano | mxnet | |
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- | 4 | |
9,852 | 20,644 | |
0.1% | - | |
5.0 | 4.1 | |
3 months ago | 6 months ago | |
Python | C++ | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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Theano
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Tracking mentions began in Dec 2020.
mxnet
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List of AI-Models
Click to Learn more...
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Introduction to deep learning hardware in the cloud
Build – Choose a machine learning framework (such as TensorFlow, PyTorch, Apache MXNet, etc.)
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just released my Clojure AI book
Clojure and Python also have bindings to the Apache MXNet library. Is there a reason why you didn't use them in some of your projects?
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Can Apple's M1 help you train models faster and cheaper than Nvidia's V100?
> But you still lose something, e.g. if you use half precision on V100 you get virtually double speed, if you do on a 1080 / 2080 you get... nothing because it's not supported.
That's not true. FP16 is supported and can be fast on 2080, although some frameworks fail to see the speed-up. I filed a bug report about this a year ago: https://github.com/apache/incubator-mxnet/issues/17665
What consumer GPUs lack is ECC and fast FP64.
What are some alternatives?
CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
Caffe - Caffe: a fast open framework for deep learning.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Caffe2
Keras - Deep Learning for humans
mlpack - mlpack: a fast, header-only C++ machine learning library
Porcupine - On-device wake word detection powered by deep learning
silero-models - Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple
Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!