v0.2.0 - Embedding layer

What's new

1. Added LayerEmbedding.
   This layer very helpful for NLP tasks.
   Implementation is inspired by this SO question: https://stats.stackexchange.com/questions/182775/what-is-an-embedding-layer-in-a-neural-network
2. Added example where Embedding has been used: https://github.com/LdDl/gan-go/tree/master/cmd/examples/train_embedding

v0.1.5 - New loss functions!

What's new

• Added next loss functions:

  • Cross entropy - https://en.wikipedia.org/wiki/Cross_entropy#Cross-entropy_loss_function_and_logistic_regression
  • Binary cross entropy - Its is cross entropy basically, but for two training classes.
  • L1 (least absolute deviations) - https://en.wikipedia.org/wiki/Least_absolute_deviations
  • Huber (pseudo) - https://en.wikipedia.org/wiki/Huber_loss#Pseudo-Huber_loss_function

• Updated MSE loss function

• Updated state of ToDo list in README.md

• Minor cleanups

Now we are moving to implement RNN stuff for LSTM purposes.

v0.1.0 - New layer types!

What's new

• Added Convolutional layer type
• Added Flatten layer type
• Added Maxpool layer type
• Added Reshape layer type
• Added Flatten layer type
• Added example of training simple CNN to classify character (not as GAN, only Discriminator) - https://github.com/LdDl/gan-go/tree/master/cmd/examples/train_cnn
• Added example of smiley face generator - https://github.com/LdDl/gan-go/tree/master/cmd/examples/generate_smiley_face
• Added some if/else statements for broadcast and batch processing
• Added reshape option into GenerateUniformTestSamples and GenerateNormTestSamples functions
• Added MSELoss function
• Added Network structure to reduce duplicating of code for .Fwd() method of each neural network type (GAN/Discriminator/Generator)
• Prepared aliases to Gorgonia's gen-functions. It could reduce confusion between 'gan.Sigmoid and gorgonia.Sigmoid'. It is on same namespace scope now.
• Updated main README.md

For more informatino see these PR's:
#1
#2

v0.0.1 - Initial version

Initial implementation of GAN

1. Ton of abstractions around Gorgonia functions
2. Little explanation in code
3. Examples for simple functions