Tutorial by Examples

The typical workflow of training and using neural networks, regardless of the library used, goes like this: Training Data Getting the training data: the X variable is the input, and the Y variable is the output. The simplest thing to do is to learn a logic gate, where X is a vector or two number...

import numpy as np #There is a lot of math in neurons, so use numpy to speed things up in python; in other languages, use an efficient array type for that language import random #Initial neuron weights should be random class Neuron: def __init__(self, nbr_inputs, weight_array = None): ...

Encog is an easy to use java neural network engine public static double XOR_INPUT[][] = { { 0.0, 0.0 }, { 1.0, 0.0 }, { 0.0, 1.0 }, { 1.0, 1.0 } }; public static double XOR_IDEAL[][] = { { 0.0 }, { 1.0 }, { 1.0 }, { 0.0 } }; public static void main(final String args[]) { /...