https://github.com/minhaskamal/intellectron
An Infant Library of Artificial Neural Network (multilayer-deep-convolutional-machine-learning)
https://github.com/minhaskamal/intellectron
artificial-neural-networks deep-learning deep-learning-library java library machine-learning machine-learning-library neural-network
Last synced: 12 months ago
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An Infant Library of Artificial Neural Network (multilayer-deep-convolutional-machine-learning)
- Host: GitHub
- URL: https://github.com/minhaskamal/intellectron
- Owner: MinhasKamal
- License: mit
- Created: 2016-05-08T13:14:38.000Z (about 10 years ago)
- Default Branch: master
- Last Pushed: 2017-08-29T02:48:39.000Z (almost 9 years ago)
- Last Synced: 2025-04-11T18:53:05.341Z (about 1 year ago)
- Topics: artificial-neural-networks, deep-learning, deep-learning-library, java, library, machine-learning, machine-learning-library, neural-network
- Language: Java
- Homepage: http://minhaskamal.github.io/Intellectron
- Size: 228 KB
- Stars: 7
- Watchers: 2
- Forks: 6
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
Intellectron
#### An Infant Library of Artificial Neural Network
The project is a simple implementation of Deep Neural Network. Several machine learning algorithms are put together here. This tiny library is particularly suitable for small projects.
### How to Use?
1. Download [Intellectron.jar](https://github.com/MinhasKamal/Intellectron/releases/download/release/Intellectron-V0.1.jar), and [integrate](https://stackoverflow.com/a/3280451/4684058) it in your project's build path.
2. Now, use it in your project like this-
```
// This is a demonstration of XOR gate implementation in Neural Network.
public static void main(String[] args) {
// For XOR gate-
// ------------------
// | input | output |
// |----------------|
// | 0 | 0 | 0 |
// | 0 | 1 | 1 |
// | 1 | 0 | 1 |
// | 1 | 1 | 0 |
// ------------------
double[][] inputs = new double[][]{
{0, 0}, {0, 1}, {1, 0}, {1, 1}
};
double[][] expectedOutputs = new double[][]{
{0}, {1}, {1}, {0}
};
// Here, we are creating four layers of neural network.
// First layer is created automatically using the input data.
// Here the input has two categories, so first layer (input layer)
// will have 2 neurons.
// The second layer will contain- 4, third layer- 2, and fourth layer
// (output layer) contains 1 neuron.
int[] numbersOfNeuronsInLayers = new int[]{4, 2, 1};
// The 'DeepNeuralNetworkImplementation' object takes the network
// structure, learning rate, and number of inputs (input categories).
DeepNeuralNetworkImplementation deepNeuralNetworkImplementation =
new DeepNeuralNetworkImplementation(numbersOfNeuronsInLayers, 0.1, 2);
// Here we are running 20,000 cycles to train the network.
// In each cycle we are passing the input and expected output.
System.out.println("# Training...\n");
int cycle = 20000;
for(int i=0; i
Intellectron is licensed under MIT License.