Welcome to the repository where I share notebooks containing implementations of state-of-the-art deep learning models from scratch using PyTorch, along with detailed explanations. This project is designed to provide you with a comprehensive understanding of these advanced models and how they work.
Note: Explanations are available in both English and Turkish for your convenience. 🌐🇬🇧🇹🇷
In this repository, you'll find a collection of Jupyter notebooks that demonstrate the step-by-step creation of state-of-the-art deep learning models. Each notebook comes with a thorough explanation of the concepts and techniques used, making it accessible to learners at various levels of expertise.
Behold the models that await your exploration:
1. Transformer: (Completed)
2. GPT-1: (Completed)
1. Vision Transformer: (Completed)
1. U-NET: (Completed)
To get started, follow these steps:
-
Clone this repository to your local machine using the following command:
git clone https://github.com/IsmailKonak/PyTorch-SOTA-Implementations.git -
Navigate to the cloned repository:
cd PyTorch-SOTA-Implementations -
Open the desired notebook using Jupyter or any compatible platform.
Feel free to explore the notebooks, experiment with the code, and learn about the inner workings of these advanced machine learning models.
💌 Email: i_konak@hotmail.com
🔗 Linkedin: Ismail Konak
If you happen upon any enigmas or questions, don't hesitate to summon assistance by opening an issue in the repository.
Happy learning and exploring the world of state-of-the-art machine learning models!