Editing Keras

[https://keras.io/callbacks/ Keras Callbacks]
[https://keras.io/getting-started/faq/#how-can-i-interrupt-training-when-the-validation-loss-isnt-decreasing-anymore how-can-i-interrupt-training-when-the-validation-loss-isnt-decreasing-anymore]

[https://keras.io/layers/embeddings/ Embeddings]

[https://github.com/fastai/courses fast.ai]

=General=
[http://picard.github.keplr.io/ Picard] - "Picard lets you easily declare large spaces of (keras) neural networks and run (hyperopt) optimization experiments on them."

[http://ankivil.com/kaggle-first-steps-with-julia-chars74k-first-place-using-convolutional-neural-networks/ Some Image Augmentation info on Kaggle]

[http://online.cambridgecoding.com/notebooks/cca_admin/neural-networks-tuning-techniques Deep learning for complete beginners: neural network fine-tuning techniques by Cambridge Coding Academy]

<strike>Look into using PRELU ELU, etc...</strike>
Look into [https://github.com/fchollet/keras/pull/2887 MPELU]

[https://keras.io/applications/ keras.io/applications/] - Inbuilt pre-trained Models.

[https://keras.io/getting-started/sequential-model-guide/ keras.io/getting-started/sequential-model-guide/] - Sequential Model Guide. Shows examples!

 predict_on_batch(self, x)

 fit_generator(self, generator, samples_per_epoch, nb_epoch, verbose=1, callbacks=None, validation_data=None, nb_val_samples=None, class_weight=None, max_q_size=10, nb_worker=1, pickle_safe=False, initial_epoch=0)

[https://arxiv.org/pdf/1512.07108v5.pdf Paper with Overview of loss/optimisation functions]

[https://uwaterloo.ca/data-science/sites/ca.data-science/files/uploads/files/keras_tutorial.pdf Keras Tutorial]

[https://github.com/fchollet/deep-learning-models Pretrained Models]

==Visualizing==
[https://blog.keras.io/how-convolutional-neural-networks-see-the-world.html how-convolutional-neural-networks-see-the-world]
[http://ankivil.com/visualizing-deep-neural-networks-classes-and-features/ visualizing-deep-neural-networks-classes-and-features]

=RNN=
[https://github.com/fchollet/keras/issues/3107 Dimension mismatch in LSTM] - Your input should be in this format (sequences, timesteps, dimensions). So based on your example, your input should be in (None, 8, 2). Your input now is (8,2).

[https://blog.keras.io/building-autoencoders-in-keras.html Building Autoencoders in Keras] - Includes LTSM!!!, Also shows a webserver graph showing progress. How to make a 2d graph. And how to interpolate between numbers...

[https://github.com/fchollet/keras/issues/1641 Help: 'Wrong number of dimensions: expected 3, got 2 with shape (...)]

[https://archive.org/details/cs231n-CNNs cs231n-CNNs 10 - Recurrent Nerual Networks Lecture]

[http://machinelearningmastery.com/time-series-prediction-lstm-recurrent-neural-networks-python-keras/ Time Series Prediction with LSTMs]

[https://github.com/mnabaee/kernels/blob/draftkernels/two-sigma/lstm-only.ipynb This guys ipython notebook]

[http://deeplearning.net/tutorial/rnnslu.html#context-window contextwindow function]

[https://keras.io/preprocessing/sequence/ Keras Sequence Preprocessing] - keras.preprocessing.sequence.pad_sequences

[https://stats.stackexchange.com/questions/184104/using-keras-lstm-rnn-for-variable-length-sequence-prediction Using Keras LSTM RNN for variable length sequence prediction] - Recomends either zero-padding or batches of 1...

[http://machinelearningmastery.com/text-generation-lstm-recurrent-neural-networks-python-keras/ Good?] - Specifically talks about sliding window. Alice in wonderland.

=GANs=
[https://arxiv.org/abs/1701.00160 GANS]

=Font Aliasing=
Can a CNN be trained to alias font glyphs. Can it work with 3D rotations?

* [https://www.reddit.com/r/rust/comments/5m20al/github_jwilmalacritty_a_crossplatform_gpu/ This Reddit post] About a GPU based terminal.

* [http://wdobbie.com/post/gpu-text-rendering-with-vector-textures/ This post about distance fields + vector textures] [https://vimeo.com/83732058 This video]

* [https://erikbern.com/2016/01/21/analyzing-50k-fonts-using-deep-neural-networks/ Analyzing 50k fonts using deep neural networks] [https://github.com/erikbern/deep-fonts github]
* [https://github.com/PistonDevelopers/freetype-rs freetype-rs]


* [https://lambdacube3d.wordpress.com/2014/11/12/playing-around-with-font-rendering/ Playing around with distance field font rendering]

* [http://www.valvesoftware.com/publications/2007/SIGGRAPH2007_AlphaTestedMagnification.pdf Valve paper]

* [http://jogamp.org/doc/gpunurbs2011/p70-santina.pdf Resolution Independent NURBS Curves Rendering using Programmable Graphics Pipeline]