nolearn 0.6.1

0.6.1 - 2019-11-05

See Github for a list of changes between this release and the last: https://github.com/dnouri/nolearn/pulls?q=is%3Apr+is%3Aclosed

0.6.0 - 2016-08-27

Thanks to @BenjaminBossan, @cancan101, @DanChianucci who greatly contributed to this release.

• lasagne: Many improvements to the nolearn.lasagne interface. Some of the more important changes:

  • Add basic support for multiple outputs https://github.com/dnouri/nolearn/pull/278

  • Extra scores can now be computed as part of Theano computation graph https://github.com/dnouri/nolearn/pull/261

  • Fix excessive memory usage in batch iterator when using shuffle https://github.com/dnouri/nolearn/pull/238

  • Add visualization code for saliency maps https://github.com/dnouri/nolearn/pull/223

  • Add method for convenient access of network’s intermediate layer output https://github.com/dnouri/nolearn/pull/196

  • Allow gradients to be scaled per layer https://github.com/dnouri/nolearn/pull/195

  • Add shuffling to BatchIterator https://github.com/dnouri/nolearn/pull/193

  • Add l1 and l2 regularization to default objective https://github.com/dnouri/nolearn/pull/169

  • Add RememberBestWeights handler: restores best weights after training https://github.com/dnouri/nolearn/pull/155

  • Passing Lasagne layer instances to ‘layers’ parameter of NeuralNet is now possible https://github.com/dnouri/nolearn/pull/146

  • Add feature visualization functions plot_loss, plot_weights, plot_activity, and plot_occlusion. The latter shows for image samples, which part of the images are crucial for the prediction https://github.com/dnouri/nolearn/pull/74

  • Add SaveWeights handler that saves weights to disk every n epochs https://github.com/dnouri/nolearn/pull/91

  • In verbose mode, print out more detailed layer information before starting with training https://github.com/dnouri/nolearn/pull/85

  • List of NeuralNet’s ‘layers’ parameter may now be formatted to contain ‘(layer_factory, layer_kwargs)’ tuples https://github.com/dnouri/nolearn/pull/73

• dbn: Added back module dbn because there’s a few online articles referencing it. Works with Python 2 only.

• Removed deprecated modules. Also deprecate grid_search module.

0.5 - 2015-01-22

• Deprecated modules console, dataset, dbn, and model.

• lasagne: Added scikit-learn compatible wrapper around the Lasagne neural network library for building simple feed-forward networks.

0.5b1 - 2014-08-09

• overfeat: Add OverFeat-based feature extractor.

• caffe: Add feature extractor based on ImageNet-pretrained nets found in caffe.

0.4 - 2014-01-15

• cache: Use joblib’s numpy_pickle instead of cPickle to persist.

0.3.1 - 2013-11-18

• convnet: Add center_only and classify_direct options.

0.3 - 2013-11-02

• convnet: Add scikit-learn estimator based on Jia and Donahue’s DeCAF.

• dbn: Change default args of use_re_lu=True and nesterov=True.

0.2 - 2013-03-03

• dbn: Add parameters learn_rate_decays and learn_rate_minimums, which allow for decreasing the learning after each epoch of fine-tuning.

• dbn: Allow -1 as the value of the input and output layers of the neural network. The shapes of X and y will then be used to determine those.

• dbn: Add support for processing sparse input data matrices.

• dbn: Improve miserable speed of DBN.predict_proba.

0.2b1 - 2012-12-30

• Added a scikit-learn estimator based on George Dahl’s gdbn in nolearn.dbn.