Python implementation of multilayer perceptron neural network from scratch.
Project description
| |Build Status|
Multilayer Neural Network in Python
-----------------------------------
Python implementation of multilayer perceptron neural network from scratch.
| Minimal neural network class with regularization using scipy minimize. Contains clear pydoc for learners to better understand each stage in the neural network.
| https://github.com/paulokuong/neural_network
Requirements
------------
- Python 3.4 (tested)
Goal
----
| To provide an example of a simple MLP for educational purpose.
Code sample
-----------
| Predicting outcome of AND logic gate:
.. code:: python
X = 000, 001, 010, 011, 100, 101, 110, 111
y = 0,0,0,0,0,0,1
Data we want to predict:
p = 011, 111, 000, 010, 111
Expected results are: 0, 1, 0, 0, 1
.. code:: python
import numpy as np
from neural_network import NeuralNetwork
X = np.matrix(
'0 0 0;0 0 1;0 1 0;0 1 1;1 0 0;1 0 1;1 1 0;1 1 1')
y = np.matrix('0;0;0;0;0;0;0;1')
n = NeuralNetwork((5,5,))
g = n.train(X, y, 0.01, show_cost=True)
y_pred = n.predict(np.matrix('0 1 1;1 1 1;0 0 0;0 1 0;1 1 1'), g)
print(y_pred)
print(n.accuracy(y_pred, np.matrix('0;1;0;0;1')))
Contributors
------------
- Paulo Kuong (`@pkuong`_)
.. _@pkuong: https://github.com/paulokuong
.. |Build Status| image:: https://travis-ci.org/paulokuong/neural_network.svg?branch=master
.. target: https://travis-ci.org/paulokuong/neural_network
Multilayer Neural Network in Python
-----------------------------------
Python implementation of multilayer perceptron neural network from scratch.
| Minimal neural network class with regularization using scipy minimize. Contains clear pydoc for learners to better understand each stage in the neural network.
| https://github.com/paulokuong/neural_network
Requirements
------------
- Python 3.4 (tested)
Goal
----
| To provide an example of a simple MLP for educational purpose.
Code sample
-----------
| Predicting outcome of AND logic gate:
.. code:: python
X = 000, 001, 010, 011, 100, 101, 110, 111
y = 0,0,0,0,0,0,1
Data we want to predict:
p = 011, 111, 000, 010, 111
Expected results are: 0, 1, 0, 0, 1
.. code:: python
import numpy as np
from neural_network import NeuralNetwork
X = np.matrix(
'0 0 0;0 0 1;0 1 0;0 1 1;1 0 0;1 0 1;1 1 0;1 1 1')
y = np.matrix('0;0;0;0;0;0;0;1')
n = NeuralNetwork((5,5,))
g = n.train(X, y, 0.01, show_cost=True)
y_pred = n.predict(np.matrix('0 1 1;1 1 1;0 0 0;0 1 0;1 1 1'), g)
print(y_pred)
print(n.accuracy(y_pred, np.matrix('0;1;0;0;1')))
Contributors
------------
- Paulo Kuong (`@pkuong`_)
.. _@pkuong: https://github.com/paulokuong
.. |Build Status| image:: https://travis-ci.org/paulokuong/neural_network.svg?branch=master
.. target: https://travis-ci.org/paulokuong/neural_network
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