https://github.com/allenvox/neural
Workspace for Neural Networks class
https://github.com/allenvox/neural
jupyter-notebook neural-networks numpy python pytorch tensorflow
Last synced: about 1 month ago
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Workspace for Neural Networks class
- Host: GitHub
- URL: https://github.com/allenvox/neural
- Owner: allenvox
- Created: 2024-09-03T05:32:46.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-15T15:43:57.000Z (8 months ago)
- Last Synced: 2025-06-15T16:39:52.540Z (8 months ago)
- Topics: jupyter-notebook, neural-networks, numpy, python, pytorch, tensorflow
- Language: Python
- Homepage:
- Size: 15.7 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Neural Networks and PyTorch Projects
This repository contains various assignments and projects related to neural networks, machine learning, and data processing using **PyTorch**. The primary focus is on exploring and implementing foundational concepts such as neural networks, activation functions, and data manipulation techniques.
## Technologies Used
- **Python**: The main programming language used for all implementations.
- **PyTorch**: A deep learning framework used for building, training, and evaluating neural networks.
- **Torchvision**: A library that provides easy access to popular datasets like MNIST and utilities for working with image data.
- **NumPy**: For numerical computations and data manipulation.
- **Jupyter Notebooks**: For interactive coding and detailed explanations of the tasks.
## Setup
To run the code and work with the notebooks, you'll need to install Python and the necessary libraries. Follow the steps below:
1. Clone the repository:
```bash
git clone https://github.com/allenvox/neural
cd neural
```
2. Install the required dependencies:
```bash
python -m pip install torch torchvision numpy jupyterlab matplotlib
```
## Usage
- The repository contains code files and Jupyter notebooks for various assignments.
- Each notebook or `.py` file is self-contained and focuses on specific concepts related to neural networks or tensor manipulation.
- You can run the notebooks or scripts locally to explore the implementations.