hisk2323 / deep-learning

deep-learning

Various Python-based neural networks, using the popular and open-source Tensorflow and Keras frameworks.
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Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Roadmap
4. Contributing
5. License
6. Contact
7. Acknowledgments

About The Project

This repository contains a large collection of various neural networks that I have worked on throughout the course of this semester. Additionally, all the necessary datasets should be included should you wish to train your own.

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Built With

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Getting Started

To get started, make sure you have Python and a suitable IDE installed on your system. If using Visual Studio Code, you will also want the extension for Jupyter Notebooks installed, though it will prompt you to do this the first time you open a .ipynb file.

Prerequisites

In addition to Python, you will need:

• A working Tensorflow installation
• Hardware capable of running neural networks, or access to a cloud service (i.e., Google Colab)

Installation

1. Clone the repo

   git clone https://github.com/hisk2323/deep-learning.git

2. Change into your directory of choice, e.g.:

   cd Raisins

3. Open the Jupyter notebook
4. Run the code, or simply look over the results already stored!

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Coming Features

• More neural networks / Jupyter notebooks

See the open issues for a current list of known issues or other planned features!

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License

Distributed under the Unlicense. See LICENSE.txt for more information.

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Contact

Project Link: https://github.com/hisk2323/deep-learning

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