Encryptix_Task_04

Sales Prediction Using Python

Overview

This project aimed to forecast future sales based on historical data. The objective was to build a predictive model that can assist businesses in making informed decisions about inventory and marketing strategies.

Data

The dataset included past sales data with features such as date, store, product, and sales volume. I performed time series analysis and used data preprocessing techniques like normalization and feature extraction.

Models and Techniques

• Linear Regression
• ARIMA (AutoRegressive Integrated Moving Average)
• Time Series Analysis
• Feature engineering and selection

Results

The model successfully predicted future sales trends with a high degree of accuracy, providing valuable insights that can help in decision-making processes for inventory management and marketing.

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