https://github.com/amplab/MLI
Data Bricks
https://github.com/databricks/spark-training
Nitro - Scala + Spark Deep Learning ML
http://www.meetup.com/SF-Bayarea-Machine-Learning/events/226657565/
repo associated with the Nitro talk. A more technical version of the slides is linked to in the README in the repo:
https://github.com/Nitro/data-pipelines
Deep Networks with Stochastic Depth
https://github.com/dblN/stochastic_depth_keras
stochastic depth training procedure trains short networks and obtains deep networks.
DEEP LEARNING (DL) CONVOLUTIONAL NEURAL NETWORKS (CNN)
http://gitxiv.com/posts/vwfa87JJp5QTXE2PJ/deep-networks-with-stochastic-depth
These notes accompany the Stanford CS class CS231n: Convolutional Neural Networks for Visual Recognition.
For questions/concerns/bug reports regarding contact Justin Johnson regarding the assignments, or contact Andrej Karpathy regarding the course notes. You can also submit a pull request directly to our git repo.
We encourage the use of the hypothes.is extension to annote comments and discuss these notes inline.
http://cs231n.github.io/
http://cs231n.github.io/neural-networks-1/
https://github.com/irusman
http://gitxiv.com/posts/vwfa87JJp5QTXE2PJ/deep-networks-with-stochastic-depth
These notes accompany the Stanford CS class CS231n: Convolutional Neural Networks for Visual Recognition.
For questions/concerns/bug reports regarding contact Justin Johnson regarding the assignments, or contact Andrej Karpathy regarding the course notes. You can also submit a pull request directly to our git repo.
We encourage the use of the hypothes.is extension to annote comments and discuss these notes inline.
http://cs231n.github.io/
http://cs231n.github.io/neural-networks-1/
https://github.com/irusman
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