https://github.com/armandfs/pytorch_study
This repository contains notebooks and scripts of everything Pytorch related that I have studied.
https://github.com/armandfs/pytorch_study
Last synced: 3 months ago
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This repository contains notebooks and scripts of everything Pytorch related that I have studied.
- Host: GitHub
- URL: https://github.com/armandfs/pytorch_study
- Owner: ArmandFS
- License: mit
- Created: 2025-11-03T22:23:38.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-11-11T10:28:31.000Z (7 months ago)
- Last Synced: 2025-11-11T12:14:50.753Z (7 months ago)
- Language: Jupyter Notebook
- Size: 1.02 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# PyTorch Study Repository!
This repository is designed to help me learn PyTorch from the ground up, with hands-on examples and progressive tutorials. All from freecodecamp and the PyTorch docs!
## 🚀 Quick Start
### Prerequisites
- Python 3.8 or higher
- pip or conda package manager
### Installation
1. **Clone or download this repository**
```bash
git clone
cd pytorch_study
```
2. **Create a virtual environment (recommended)**
```bash
# Using venv
python -m venv pytorch_env
# Activate the environment
# On Windows:
pytorch_env\Scripts\activate
# On macOS/Linux:
source pytorch_env/bin/activate
```
3. **Install dependencies**
```bash
pip install -r requirements.txt
```
4. **Verify installation**
```bash
python -c "import torch; print(f'PyTorch version: {torch.__version__}')"
```
## 📁 Project Structure
```
pytorch_study/
├── notebooks/ # Jupyter notebooks for learning
│ ├── 01_pytorch_basics.ipynb
│ ├── 02_neural_networks.ipynb
│ ├── 03_computer_vision.ipynb
│ └── 04_natural_language_processing.ipynb
├── data/ # Datasets and data files
├── models/ # Saved model checkpoints
├── utils/ # Utility functions and helpers
├── examples/ # Standalone example scripts
├── requirements.txt # Python dependencies
├── .gitignore # Git ignore rules
└── README.md # This file
```
## 📚 Learning Path
### 1. **PyTorch Basics** (`notebooks/01_pytorch_basics.ipynb`)
- Tensors and operations
- Automatic differentiation
- Basic neural network construction
- Training loops
### 2. **Neural Networks** (`notebooks/02_neural_networks.ipynb`)
- Building different types of neural networks
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Transfer learning
### 3. **Computer Vision** (`notebooks/03_computer_vision.ipynb`)
- Image preprocessing and augmentation
- CNN architectures
- Object detection
- Image segmentation
### 4. **Natural Language Processing** (`notebooks/04_natural_language_processing.ipynb`)
- Text preprocessing
- Word embeddings
- RNNs and LSTMs for NLP
- Transformer models
## 🛠️ Getting Started with Jupyter
1. **Start Jupyter Notebook**
```bash
jupyter notebook
```
2. **Or start JupyterLab (recommended)**
```bash
jupyter lab
```
3. **Navigate to the `notebooks/` folder and start with `01_pytorch_basics.ipynb`**
## 💡 Tips for Learning
1. **Start with the basics**: Work through the notebooks in order
2. **Experiment**: Modify the code, try different parameters
3. **Practice**: Create your own small projects
4. **Read the documentation**: PyTorch docs are excellent
5. **Join the community**: PyTorch forums and Discord are great resources
## 🔧 Common Commands
### Check PyTorch installation
```python
import torch
print(f"PyTorch version: {torch.__version__}")
print(f"CUDA available: {torch.cuda.is_available()}")
```
### Create a simple tensor
```python
import torch
x = torch.tensor([1, 2, 3, 4])
print(x)
```
### Basic neural network
```python
import torch.nn as nn
class SimpleNet(nn.Module):
def __init__(self):
super(SimpleNet, self).__init__()
self.fc = nn.Linear(10, 1)
def forward(self, x):
return self.fc(x)
model = SimpleNet()
```
## 📖 Additional Resources
- [PyTorch Official Tutorials](https://pytorch.org/tutorials/)
- [PyTorch Documentation](https://pytorch.org/docs/)
- [Deep Learning with PyTorch Book](https://pytorch.org/deep-learning-with-pytorch)
- [PyTorch Examples on GitHub](https://github.com/pytorch/examples)
## 🤝 Contributing
Feel free to:
- Add your own examples
- Improve existing notebooks
- Fix bugs or typos
- Suggest new topics
## 📝 License
This project is for educational purposes. Feel free to use and modify as needed.
---
Happy learning! 🎉 If you have any questions, don't hesitate to ask or check the PyTorch community forums.