Simple and powerfull neural network library for python
Neurolab is a simple and powerful Neural Network Library for Python. Contains based neural networks, train algorithms and flexible framework to create and explore other neural network types.
Pure python + numpy
API like Neural Network Toolbox (NNT) from MATLAB
Interface to use train algorithms form scipy.optimize
Flexible network configurations and learning algorithms. You may change: train, error, initialization and activation functions
Unlimited number of neural layers and number of neurons in layers
Variety of supported types of Artificial Neural Network and learning algorithms
>>> import numpy as np >>> import neurolab as nl >>> # Create train samples >>> input = np.random.uniform(-0.5, 0.5, (10, 2)) >>> target = (input[:, 0] + input[:, 1]).reshape(10, 1) >>> # Create network with 2 inputs, 5 neurons in input layer and 1 in output layer >>> net = nl.net.newff([[-0.5, 0.5], [-0.5, 0.5]], [5, 1]) >>> # Train process >>> err = net.train(input, target, show=15) Epoch: 15; Error: 0.150308402918; Epoch: 30; Error: 0.072265865089; Epoch: 45; Error: 0.016931355131; The goal of learning is reached >>> # Test >>> net.sim([[0.2, 0.1]]) # 0.2 + 0.1 array([[ 0.28757596]])
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