python - 神经网络示例源代码(最好是 Python)

Question

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Answer 1

在 ubuntu 论坛上发现了这个有趣的讨论 http://ubuntuforums.org/showthread.php?t=320257

import time
import random

# Learning rate:
# Lower  = slower
# Higher = less precise
rate=.2

# Create random weights
inWeight=[random.uniform(0, 1), random.uniform(0, 1)]

# Start neuron with no stimuli
inNeuron=[0.0, 0.0]

# Learning table (or gate)
test =[[0.0, 0.0, 0.0]]
test+=[[0.0, 1.0, 1.0]]
test+=[[1.0, 0.0, 1.0]]
test+=[[1.0, 1.0, 1.0]]

# Calculate response from neural input
def outNeuron(midThresh):
    global inNeuron, inWeight
    s=inNeuron[0]*inWeight[0] + inNeuron[1]*inWeight[1]
    if s>midThresh:
        return 1.0
    else:
        return 0.0

# Display results of test
def display(out, real):
        if out == real:
            print str(out)+" should be "+str(real)+" ***"
        else:
            print str(out)+" should be "+str(real)

while 1:
    # Loop through each lesson in the learning table
    for i in range(len(test)):
        # Stimulate neurons with test input
        inNeuron[0]=test[i][0]
        inNeuron[1]=test[i][1]
        # Adjust weight of neuron #1
        # based on feedback, then display
        out = outNeuron(2)
        inWeight[0]+=rate*(test[i][2]-out)
        display(out, test[i][2])
        # Adjust weight of neuron #2
        # based on feedback, then display
        out = outNeuron(2)
        inWeight[1]+=rate*(test[i][2]-out)
        display(out, test[i][2])
        # Delay
        time.sleep(1)

编辑:还有一个名为 chainer 的框架 https://pypi.python.org/pypi/chainer/1.0.0