Update README.md

README.md

@@ -1,13 +1,75 @@
-# Java-Neural-Network
-## A neural network in Java from scratch without libraries or API's.
 
- #### Note: This is a template for other neural networks but standalone, it checks whether a float array is sorted ascendingly, descendingly or not at all.
+# Java Neural Network
+[![Generic badge](https://img.shields.io/badge/Java-NeuralNetwork-green.svg)](https://shields.io/)
+[![Build Status](https://img.shields.io/badge/build-passing-brightgreen.svg)](https://shields.io/)
+[![Version](https://img.shields.io/badge/version-1.2.1-blue.svg)](https://shields.io/)
+[![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://shields.io/)
 
+## Overview
+Java Neural Network is an innovative project aimed at implementing a neural network purely in Java without the use of external libraries or APIs. It is designed to be a flexible and extendable framework for various neural network experiments.
 
- A result of 1, 0, 0 means the array the AI thinks the array is sorted ascendingly. 
+### Features
+- Pure Java implementation
+- Customizable neural network architecture
+- No external dependencies
+- Simple and intuitive API
+- Comprehensive documentation and examples
+
+## Getting Started
+These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
+
+### Prerequisites
+- Java JDK 1.8 or later
+- Basic understanding of neural networks and Java programming
+
+### Installation
+1. Clone the repository:
+   ```
+   git clone https://github.com/noahbclarkson/Java-Neural-Network.git
+   ```
+2. Navigate to the cloned directory:
+   ```
+   cd Java-Neural-Network
+   ```
+3. Compile and run the project using your preferred Java IDE or command line tools.
+
+## Usage
+The Java Neural Network can be used to create, train, and test neural network models for various applications such as pattern recognition, data classification, and more.
+
+### Example
+Here is a simple example of using the Java Neural Network to train a model:
+
+```java
+import unprotesting.com.github.*;
+
+public class Example {
+    public static void main(String[] args) {
+        // Create and train the neural network
+        NeuralNetwork network = new NeuralNetwork();
+        network.train(trainingData);
+
+        // Test the neural network
+        float[] testInput = { ... };
+        float[] output = network.predict(testInput);
+        System.out.println("Predicted output: " + Arrays.toString(output));
+    }
+}
+```
+
+## Authors
+- **Noah B. Clarkson** - *Initial work* - [noahbclarkson](https://github.com/noahbclarkson)
+
+## License
+This project is licensed under the Apache License 2.0 - see the [LICENSE.md](LICENSE.md) file for details
+
+## Note
+
+This is a template for other neural networks but standalone, it checks whether a float array is sorted ascendingly, descendingly or not at all.
+
+- A result of 1, 0, 0 means the array the AI thinks the array is sorted ascendingly. 
 
- A result of 0, 1, 0 means the the AI thinks the array is sorted descendingly. 
+- A result of 0, 1, 0 means the the AI thinks the array is sorted descendingly. 
 
- A result of 0, 0, 1 means the AI thinks the array is not sorted.
+- A result of 0, 0, 1 means the AI thinks the array is not sorted.
 
- A result of 0, 0, 0 means the AI does not know / an error.
+- A result of 0, 0, 0 means the AI does not know / an error.