Welcome to the PyTorch Exploration Repository! This repository serves as a playground for exploring and experimenting with PyTorch, a powerful open-source machine learning library. In this repository, I am exploring its capabilities by using baby datasets and finding out more about PyTorch 🔥. Whether you're a beginner looking to dive into the world of deep learning or an experienced practitioner seeking new insights, this repository provides a variety of code snippets, tutorials, and projects to enhance your understanding and skills with PyTorch along with me.
PyTorch is a widely used deep learning framework that provides a flexible and dynamic computational graph, making it a popular choice for researchers and developers. This repository is dedicated to exploring different aspects of PyTorch, including but not limited to:
- Core functionalities
- Neural network architectures
- Transfer learning
- Data preprocessing and augmentation
- Model interpretation and visualization
- Deployment strategies
Feel free to explore, learn, and contribute to the repository!
To get started with the PyTorch Exploration Repository, follow these steps:
- Clone the Repository:
git clone https://github.com/your-username/pytorch-exploration.git
or visit PyTorch for further (official) instructions!
- Explore the Codebase: Browse through the files to find code snippets, tutorials, and projects.
The repository is organized into several files, each focusing on a specific aspect of PyTorch exploration. Here's a brief overview:
- 00_pytorch_fundamentals.ipynb : I go through fundamental aspects of using PyTorch
- 01_pytorch_workflow.ipynb : The several key steps of the workflow while using PyTorch
- 02_pytorch_classification.ipynb : Exploring classificaiton problem using PyTorch. Binary and Multiclass Classification
- 04_pytorch_custom_datasets.ipynb : Creating, exploring and using a custom dataset.