Sales Forecasting Using Machine Learning Techniques

This project focuses on predicting future sales based on historical sales data using advanced machine learning techniques. The goal is to provide accurate sales forecasts that can help businesses optimize inventory, improve marketing strategies, and make data-driven decisions.

Features

• Analyzes historical sales data to predict future trends.
• Uses advanced machine learning models like ARIMA, LSTM, and Random Forest.
• Provides visual insights into sales trends and forecast accuracy.
• Supports different time intervals (daily, weekly, monthly).

Installation

Follow these steps to set up the sales forecasting system on your local machine:

1. Clone the Repository

   git clone https://github.com/username/sales-forecasting.git
   cd sales-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 the sales forecasting analysis, run the main script with your sales data:

python forecast.py --input