Keras

Keras Callbacks how-can-i-interrupt-training-when-the-validation-loss-isnt-decreasing-anymore

Embeddings

fast.ai

General

Look into using PRELU ELU, etc... Look into MPELU

keras.io/applications/ - Inbuilt pre-trained Models.

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)

Paper with Overview of loss/optimisation functions

This has lots of good infos - Includes an AndrewNG talk and recommended papers. (Should be in ML?)

Reddit best papers (Should be in ML?)

Keras Tutorial

Pretrained Models

RNN

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).

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...

Help: 'Wrong number of dimensions: expected 3, got 2 with shape (...)

cs231n-CNNs 10 - Recurrent Nerual Networks Lecture

Time Series Prediction with LSTMs

This guys ipython notebook

contextwindow function

Keras Sequence Preprocessing - keras.preprocessing.sequence.pad_sequences

Using Keras LSTM RNN for variable length sequence prediction - Recomends either zero-padding or batches of 1...

Good? - Specifically talks about sliding window. Alice in wonderland.

GANs

GANS

Font Aliasing

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

• This Reddit post About a GPU based terminal.

• This post about distance fields + vector textures This video

• Analyzing 50k fonts using deep neural networks github
• freetype-rs

• Playing around with distance field font rendering

• Valve paper

• Resolution Independent NURBS Curves Rendering using Programmable Graphics Pipeline