ML-PaperImplementations

Welcome to the ML-PaperImplementations repository! This is a collection of machine learning paper implementations, intended as a resource for researchers, students, and enthusiasts in the field.

Papers Implemented

1. alexnet - ImageNet Classification with Deep Convolutional Neural Networks (NIPS 2012)
2. vae - Auto-Encoding Variational Bayes (ICLR 2014)
3. gan - Generative Adversarial Networks (NIPS 2014)
4. u-net - U-Net: Convolutional Networks for Biomedical Image Segmentation (MICCAI 2015)
5. neural-style-transfer - A Neural Algorithm of Artistic Style (arXiv 2015)
6. resnet - Deep Residual Learning for Image Recognition (CVPR 2016)

Usage

Each paper implementation is contained in its own directory within the repository. To run a particular implementation, navigate to the corresponding directory and follow the instructions provided in the README.md file for that implementation.

Installation

To set up a development environment to run the code, please follow these steps:

1. Clone the repository:

git clone https://github.com/emirhanboge/CV-Paper-Implementations.git

2. Navigate to the project directory:

cd CV-Paper-Implementations

3. Create a virtual environment:

python -m venv venv

4. Activate the virtual environment:

source venv/bin/activate

5. Upgrade pip:

pip install --upgrade pip

6. Install the required packages:

pip install -r requirements.txt