https://github.com/felixkamau/neuralnetwork
Custom Neural Network Implementation in Python Welcome to my repository featuring a custom implementation of a neural network in Python! This project aims to provide a hands-on exploration of neural network fundamentals by building a neural network from scratch, without relying on external libraries.
https://github.com/felixkamau/neuralnetwork
machine-learning neural-networks
Last synced: 3 months ago
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Custom Neural Network Implementation in Python Welcome to my repository featuring a custom implementation of a neural network in Python! This project aims to provide a hands-on exploration of neural network fundamentals by building a neural network from scratch, without relying on external libraries.
- Host: GitHub
- URL: https://github.com/felixkamau/neuralnetwork
- Owner: felixkamau
- License: mit
- Created: 2024-02-10T08:29:48.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-02-10T14:48:03.000Z (over 1 year ago)
- Last Synced: 2025-01-08T11:47:26.816Z (5 months ago)
- Topics: machine-learning, neural-networks
- Language: Python
- Homepage:
- Size: 7.81 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Neuralnetwork
Custom Neural Network Implementation in Python Welcome to my repository featuring a custom implementation of a neural network in Python! This project aims to provide a hands-on exploration of neural network fundamentals by building a neural network from scratch, without relying on external libraries.
# Key Features:
**Modular Architecture**: The neural network is designed with modularity in mind, making it easy to customize network architecture, activation functions, and optimization algorithms.
**Forward and Backward Pass**: Implements both forward and backward passes necessary for training the neural network.
**Activation Functions:** Supports popular activation functions like the sigmoid function and their derivatives.
**Training Functionality:** Includes training functionality with the ability to specify epochs and learning rate.
Demonstration with XOR Problem: Demonstrates the neural network's capabilities by solving the classic XOR problem.
Educational Resource: Serves as an educational resource for understanding the inner workings of neural networks.
**Usage:**
# Clone the repository.
**Import the NeuralNetwork class** into your Python project.
Define your dataset and instantiate the neural network with the desired architecture.
Train the neural network by calling the train method with your dataset.
Evaluate the trained model's performance and make predictions using the forward_pass method.
Contributions:
Contributions and feedback are highly encouraged! Whether it's bug fixes, performance improvements, or additional features, feel free to contribute by opening a pull request or raising an issue.
**Acknowledgements:**
Inspired by the spirit of learning and exploration in the field of neural networks.
Let's dive into the world of neural networks together, building understanding one step at a time!
Usage:
Clone the repository.
Import the NeuralNetwork class into your Python project.
Define your dataset and instantiate the neural network with the desired architecture.
Train the neural network by calling the train method with your dataset.
Evaluate the trained model's performance and make predictions using the forward_pass method.
Contributions:
Contributions and feedback are highly encouraged! Whether it's bug fixes, performance improvements, or additional features, feel free to contribute by opening a pull request or raising an issue.
**
Acknowledgements:**
**Contributions and feedback are highly encouraged! Whether it's bug fixes, performance improvements, or additional features, feel free to contribute by opening a pull request or raising an issue.**
**Acknowledgements:**
Inspired by the spirit of learning and exploration in the field of neural networks.
Let's dive into the world of neural networks together, building understanding one step at a time!