Neural-Network

# AI & Deep Learning Projects

This repository contains implementations and tools related to deep learning, GANs, and code review automation.

## Projects / Files

### 1. `CodeReviewer.ipynb`
An AI agent that **reviews Python code** and generates a structured report.  
**Features:**
- Analyzes code quality, structure, and best practices.
- Highlights potential bugs or inefficiencies.
- Generates a summary report with suggestions for improvement.

### 2. `GAN_using_nn.ipynb`
Implementation of a **Generative Adversarial Network (GAN)** using neural networks from scratch.  
**Features:**
- Demonstrates GAN architecture with generator and discriminator networks.
- Trains a model on sample datasets.
- Visualizes generated outputs during training.

### 3. `nn_stepby_step.ipynb`
Step-by-step implementation of **Neural Networks** for learning purposes.  
**Features:**
- Explains neural network layers, forward and backward propagation.
- Includes detailed code with comments for understanding model training.
- Supports experimentation with different architectures.

## Getting Started

1. Clone the repository:
```bash
git clone <repo-url>

2. Install dependencies:

pip install -r requirements.txt

3. Run Jupyter notebooks:

jupyter notebook

Tech Stack

• Languages: Python
• Libraries/Frameworks: PyTorch, NumPy, Matplotlib, Pandas
• Tools: Jupyter Notebook, Google Colab

Author

Maha Rehan – GitHub body { font-family: 'Helvetica', sans-serif; line-height: 1.6; color: #333; background-color: #f5f5f5; padding: 20px; }

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