Neuralnetwork - Basic Multilayer Perceptron Neural Network for deep learning

Last update: Nov 01, 2022

Related tags

Deep Learning neuralnetwork

Overview

Neural Network

Just a basic Neural Network module

Usage Example

Importing Module

from neuralnetwork import NeuralNetwork
import numpy as np

Initiating

Initiate NeuralNetwork class with parameters:

NeuralNetwork(input_nodes: int, hidden_nodes: int, output_nodes: int)

model = NeuralNetwork(3, 2, 1)

Set 3 inputs nodes, 2 hidden nodes, and 1 output node

Training

For this example, we want to train our machine with data below. Basically, our expected output are just the first number of inputs.

[0, 0, 1] = 0
[0, 1, 0] = 0
[1, 0, 1] = 1
[1, 1, 0] = 1

Set training data for inputs and target outputs, and train with train(inputs, targets) method through some number of iterations, until you statisfied. This example: 20000 iterations

# Training data inputs
inputs = np.array([
    [0, 0, 1],
    [0, 1, 0],
    [1, 0, 1],
    [1, 1, 0],
])
# Training data target outputs
targets = np.array([[0, 0, 1, 1]]).T

# iterate to train
for i in range(20000):
    model.train(inputs, targets)

Predicting

After a training above, now we test our machine to predict an output for given input.

Example: [0, 1, 1] should produce 0, because 0 is the first number.

# Question
question = np.array([[0, 1, 1 ]])
print("Question:")
print(question)
# Prediction
prediction = model.think(question)
print("Prediction:")
print(prediction)

Result

This is the terminal result

Training Data
[[0 0 1]
 [0 1 0]
 [1 0 1]
 [1 1 0]]
Training Target
[[0]
 [0]
 [1]
 [1]]
...
target output after training
[[0.00344796]
 [0.00344796]
 [0.99647399]
 [0.99647399]]
---------------
Question:
[[0 1 1]]
Prediction:
[[0.00332841]]

From [0, 1, 1] input, we predict: 0.003 (almost nearly zero)

Woohoo! You just build your machine learning

How we know our accurracy?

The "target output after training" above should match nearly the "training target" actual data.

Full example is located in examples/basic.py file

Project Structure

/
├── neuralnetwork.py    # core module
├── pyproject.toml
├── README.rst
├── examples             # containing examples of usage
│   ├── basic.py        # basic usage example
│   └── __init__.py
└── tests
    ├── __init__.py
    └── *.py

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Neuralnetwork - Basic Multilayer Perceptron Neural Network for deep learning

Related tags

Overview

Neural Network

Usage Example

Importing Module

Initiating

Training

Predicting

Result

Project Structure

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Releases(v0.1.0)

v0.1.0(Jan 24, 2022)

Owner

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