Demand Forecasting for Inventory Management

This project aims to forecast product demand to enhance inventory management. By predicting future demand, businesses can optimize stock levels, minimize costs, and prevent stockouts or overstock situations.

Features

• Forecasts demand for individual products using historical sales data.
• Utilizes models such as ARIMA, Prophet, and LSTM for time series forecasting.
• Provides actionable insights for replenishment planning and inventory optimization.
• Visualizes historical vs. forecasted demand to identify trends and anomalies.

Installation

To set up the demand forecasting system on your local machine, follow these steps:

1. Clone the Repository

   git clone https://github.com/username/demand-forecasting.git
   cd demand-forecasting

2. Set Up Virtual Environment (Optional but Recommended)

   python3 -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install Required Packages

   pip install -r requirements.txt

Usage

To start forecasting demand, run the main script with your sales data:

python demand_forecasting.py --input