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: 30 days 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 (6 months ago)
• Default Branch: main
• Last Pushed: 2025-01-12T13:53:13.000Z (about 1 month ago)
• Last Synced: 2025-01-12T14:41:15.920Z (about 1 month ago)
• Topics: jupyter-notebook, neural-networks, numpy, python, pytorch, tensorflow
• Language: Python
• Homepage:
• Size: 432 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Neural Networks and PyTorch Projects

![Github last commit](https://img.shields.io/github/last-commit/allenvox/neural)


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.