Neuralnetlib

- feat(optimizers): add AdaBelief
- feat(optimizers): add RAdam
- feat(loss): add focal loss
- fix(optimizers-losses-activations): from_config
- feat(ensemble): add XGBoost
- feat(layer): add ActivationFunction init as string in Activation
- ci: bump version to 4.0.4

- refactor: some improvements
- feat: add validation_split parameter to fit method
- fix(lstm): vanishing and exploding gradient issue
- docs: update readme
- ci: bump version to 4.0.3

- feat(ensemble): add AdaBoost
- feat(ensemble): add GradientBoostingMachine
- ci: bump version to 4.0.2

- docs: add gif into notebook
- feat(GAN): auto sizing for epoch plot
- feat: add data imputation
- feat(ensemble): add IsolationForest
- feat(ensemble): add RandomForest
- feat(cluster): add KMeans
- feat(cluster): add DBSCAN
- docs: update readme

- feat: add GAN
- fix(GAN): weights and backpropagation
- refactor(BatchNormalization): more stable training
- fix(GAN): some fixes and general improvements
- feat(Loss): add WGAN loss
- feat(WGAN): improve generation
- ci: bump version to 3.3.9
- fix(WGAN): discriminator training on both real and fake data
- feat(GAN): improve image generation
- fix(Transformer): yet another mode collapse fix
- feat(layers): better gradient scaling and stability
- feat(Tokenizer): add BPE tokenize mode
- docs: update readme
- ci: bump version to 4.0.0

- feat: add GAN
- fix(GAN): weights and backpropagation
- refactor(BatchNormalization): more stable training
- fix(GAN): some fixes and general improvements
- feat(Loss): add WGAN loss
- feat(WGAN): improve generation
- ci: bump version to 3.3.9