Sales Prediction and Retail Data Analysis

This repository contains files related to sales prediction and retail data analysis using machine learning models. The dataset used in these analyses includes the following files:

1. melb_data.csv

   • This file contains data related to Melbourne housing, which may be used for various data analysis or machine learning tasks.

2. train.csv

   • The training dataset used for developing machine learning models.

3. Decision_Tree_Regression_Model

   • A Jupyter Notebook created using Colaboratory demonstrates the implementation of a Decision Tree Regression model for retail data analysis. It is used for predicting sales based on the provided data.

4. Retail_Data_Analysis_using_Random_Forest_ML_Model

   • Another Jupyter Notebook created using Colaboratory that focuses on retail data analysis using a Random Forest machine learning model.

5. Sales_Prediction_using_DecisionTreeRegressor_Model and Random Forest Model

   • These two Jupyter Notebooks were created using Colaboratory, specifically targeting sales prediction using a Decision Tree Regressor model and random forest model.

Usage

• Decision_Tree_Regression_Model.ipynb and Sales_Prediction_using_DecisionTreeRegressor_Model.ipynb provide examples of how to use machine learning models for sales prediction.

• Retail_Data_Analysis_using_Random_Forest_ML_Model.ipynb and Retail_Data_Analysis_using_Random_Forest_Model.ipynb focuses on retail data analysis using a Random Forest machine learning model.