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Commits on Aug 20, 2013

• Added a plot of the really bad MNIST images

  mnielsen

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• Cleaning up mnist_svm

  mnielsen

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• Minor improvements to mnist_average_darkness

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• Minor sharpening

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Commits on Aug 19, 2013

• Fixing conflicts

  mnielsen

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  5ecc7a1

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• Removed regularization from network_basic

  mnielsen

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Commits on Aug 18, 2013

• Removed unused cost function

  mnielsen

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• Minor improvements to comments

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Commits on Aug 17, 2013

• Minor refactoring of network_basic

  mnielsen

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  156673a

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• Adding (compressed) MNIST data

  mnielsen

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Commits on Aug 15, 2013

• Reorganizing figures

  mnielsen

  committed
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• Changing axis labels

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Commits on Aug 9, 2013

• Actually added image this time...

  mnielsen

  committed
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• Added complete zero image from MNIST data

  mnielsen

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Commits on Aug 6, 2013

• Added 10 by 10 array of MNIST digits

  mnielsen

  committed
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Commits on Jul 19, 2013

• Renaming of the book

  mnielsen

  committed
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• Rationalized the data format in mnist_loader, and minor improvements and simplifications for network_basic

  mnielsen

  committed
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Commits on Jul 18, 2013

• Adding network_basic.py

  mnielsen

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Commits on May 11, 2013

• Added graph for rectified linear unit

  mnielsen

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• Added plot of tanh

  mnielsen

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Commits on May 4, 2013

• Bug fixes

  mnielsen

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• Bugfixing deep_learning

  mnielsen

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• Bugfixing in deep_learning

  mnielsen

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Commits on May 2, 2013

• Added deep_learning module

  mnielsen

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• Refactoring DeepAutoencoder

  mnielsen

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  b5c9464

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• Improved image

  mnielsen

  committed
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• Adding plot for a deep autoencoder

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Commits on May 1, 2013

• Improving comments

  mnielsen

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Commits on Apr 29, 2013

• Minor refactoring

  mnielsen

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  91821a2

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• Added plot of how the gradient of the cost function varies with layer

  mnielsen

  committed
  86c4c6b

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• Refactoring and consolidating the feedforward methods

  mnielsen

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  70c60bf

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• Refactoring the propagation of data

  mnielsen

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Commits on Apr 26, 2013

• Added a baseline comparison

  mnielsen

  committed
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• Typo

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• The error is now l1 error

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