NeuPy is a Python library for Artificial Neural Networks.
$ pip install neupy
- Password recovery
- Discrete Hopfield Network
- Boston house-prices dataset
- Visualize Backpropagation Algorithms
- MNIST, Multilayer perceptron
- Rectangle images, Multilayer perceptron
- MNIST, Denoising Autoencoder
- Boston House Price prediction, Hessian algorithm
- Learning Algorithms Visualization, Gradient Descent, Momentum, RPROP and Conjugate Gradient
- IMDB review classification using CBOW and RPROP MLP
- Classify iris dataset, Probabilistic Neural Network (PNN)
- Regression using Diabetes dataset, Generilized Neural Nerwork (GRNN)
- Music-Speech audio classification, Probabilistic Neural Network (PNN)
- Sinus function approximation, CMAC
- Visualize Discrete Hopfield Neural Network energy function
- Password recovery, Discrete Hopfield Neural Network
- Python 2.7, 3.4
- Theano >= 0.8.1
- NumPy >= 1.9.0
- SciPy >= 0.14.0
- Matplotlib >= 1.4.0
- Adding reccurent neural network layers (Issue #57)
- Bug fixing and version stabilization (Known bugs)
- Speeding up algorithms
- Adding more algorithms
- Algorithms that use Backpropagation training approach
- Classic Gradient Descent
- Mini-batch Gradient Descent
- Conjugate Gradient
- Fletcher-Reeves
- Polak-Ribiere
- Hestenes-Stiefel
- Conjugate Descent
- Liu-Storey
- Dai-Yuan
- quasi-Newton with Wolfe search
- BFGS
- DFP
- PSB
- SR1
- Levenberg-Marquardt
- Hessian (Newton's method)
- Hessian diagonal
- Momentum
- Nesterov Momentum
- RPROP
- iRPROP+
- QuickProp
- Adadelta
- Adagrad
- RMSProp
- Adam
- AdaMax
- Algorithms that penalize weights
- Weight Decay
- Weight Elimination
- Algorithms that update learning rate
- Adaptive Learning Rate
- Error difference Update
- Linear search using Golden Search or Brent
- Search than converge
- Simple Step Minimization
- Ensembles
- Mixture of Experts
- Dynamically Averaged Network (DAN)
- Neural Networks with Radial Basis Functions (RBFN)
- Generalized Regression Neural Network (GRNN)
- Probabilistic Neural Network (PNN)
- Radial basis function K-means
- Autoasociative Memory
- Discrete BAM Network
- CMAC Network
- Discrete Hopfield Network
- Competitive Networks
- Adaptive Resonance Theory (ART1) Network
- Self-Organizing Feature Map (SOFM or SOM)
- Linear networks
- Perceptron
- LMS Network
- Modified Relaxation Network
- Associative
- OJA
- Kohonen
- Instar
- Hebb