synadart 0.4.1+1
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Library for creating neural networks, with a purely Dart implementation.
0.1.0 #
- Added Multi-layer Perceptron and a basic algorithm for backpropagation
0.1.1 #
- Added README.md, updated formatting
0.2.0 #
- Added FF ( feedforward ) and simple Perceptron networks
- Added LReLU, eLU and tanh activation function
- Renamed 'sigmoid' to 'logistic' function
0.2.1 #
- Removed FF ( feedforward ) and simple Perceptron networks in favour of an upcoming simpler implementation of basically the same idea, through just one network model.
- Added [learningRate] as a parameter, and removed the hard-coded value of 0.2.
- Organised the files slightly
- Updated documentation of
Neuron
0.2.2 #
- Updated documentation of
Layerand removed a chunk of dead code.
0.2.3 #
- Updated documentation of
Network. - Replaced
process()inLayerwith anoutputgetter, simplifying the implementation of getting eachNeuron's output.
0.2.4 #
- Updated documentation of
activation.dart, having added explanations for the different activation functions.
0.2.5 #
- Renamed
Multilayer PerceptrontoDeep Feed-forward, which should be a more fitting and future-proof name.
0.3.0 #
- Updated documentation of
Logger,BackpropagationandValueGenerator. - Created
examplesfolder with arecognise_5example that allows for recognition of the number '5'.
0.3.1 #
- Added 5 new activation functions:
SeLU,Softplus,Softsign,SwishandGaussian. - Renamed the
logisticfunction tosigmoid. - Added
absfunction for obtaining the absolute of a value tomathematical_operations.
0.3.2 #
- Added simple feed-forward network model.
0.4.0 #
- Code organisation.
- Replacing network types such as
feed-forwardordeep feed-forwardwith a simpleSequential. - Moved focus from
NetworktoLayer, so that different layers can be added to aNetwork, rather than creating new types of networks, and limiting the user to a preset model. - Updated example code and README.md
0.4.1 #
- Updated documentation
0.4.1+1 #
- Refactoring code
- Removing
logger.dartin favour ofSprint