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12 Questions

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Does feature scaling have any benefits if all features are on the same scale?

Feb 24 at 19:10 Abhishek Verma 367

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Should we also shuffle the test dataset when training with SGD?

machine-learning training datasets stochastic-gradient-descent testing

Nov 3 at 13:57 nbro♦ 25.4k

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answer

106

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Applications of Information Theory in Machine Learning

machine-learning deep-learning information-theory

Nov 23 at 1:57 nbro♦ 25.4k

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Image classification on SVG format

neural-networks convolutional-neural-networks image-recognition

Aug 5 at 5:12 SpiderRico 527

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Is there any application of topology to deep learning?

deep-learning theory topology

May 3 at 23:37 DukeZhou♦ 6,010

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123

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What are examples of machine learning techniques inspired by neuroscience?

machine-learning neuromorphic-engineering spiking-neural-networks neuroscience reservoir-computing

Apr 22 at 16:35 nbro♦ 25.4k

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Why do momentum techniques not work well for RNNs?

recurrent-neural-networks gradient-descent stochastic-gradient-descent momentum

Dec 13 at 12:37 nbro♦ 25.4k

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Machine learning frameworks for esoteric languages [closed]

machine-learning programming-languages resource-request

Feb 13 '20 at 18:53 SpiderRico 527

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147

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Is there a reason to use TensorFlow over PyTorch for research purposes?

deep-learning tensorflow comparison research pytorch

Feb 13 '20 at 2:08 nbro♦ 25.4k

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answer

168

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Should I prefer the model with the lowest validation loss or the highest validation accuracy to deploy?

neural-networks deep-learning applications overfitting early-stopping

Nov 22 at 18:03 Community♦ 1

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Are there optimizers that schedule their learning rate, momentum etc. autonomously?

optimization hyperparameter-optimization adam

Feb 6 '20 at 18:43 SpiderRico 527

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104

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Is there a reason to choose regular momentum over Nesterov momentum for neural networks?

neural-networks comparison loss-functions gradient-descent hyperparameter-optimization

Feb 5 '20 at 6:48 Ketil Malde 114

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12 Questions

Does feature scaling have any benefits if all features are on the same scale?

Should we also shuffle the test dataset when training with SGD?

Applications of Information Theory in Machine Learning

Image classification on SVG format

Is there any application of topology to deep learning?

What are examples of machine learning techniques inspired by neuroscience?

Why do momentum techniques not work well for RNNs?

Machine learning frameworks for esoteric languages [closed]

Is there a reason to use TensorFlow over PyTorch for research purposes?

Should I prefer the model with the lowest validation loss or the highest validation accuracy to deploy?

Are there optimizers that schedule their learning rate, momentum etc. autonomously?

Is there a reason to choose regular momentum over Nesterov momentum for neural networks?