GitHub - 11-andy-11/RetailReturnsML: A machine learning project to predict product return amounts based on brand, sales, advertising spend, and order data. Includes data preprocessing, exploratory data analysis (EDA), feature encoding, scaling, model training with Random Forest, evaluation, and saving the trained model for future predictions.

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
Countplot		Countplot
ParteaI		ParteaI
countplot		countplot
grafice_relatii_target		grafice_relatii_target
heatmap		heatmap
histograme		histograme
Brand_Sales_AdSpend_Data.csv		Brand_Sales_AdSpend_Data.csv
Brand_Sales_AdSpend_Data.csv:Zone.Identifier		Brand_Sales_AdSpend_Data.csv:Zone.Identifier
Ion_Andrei_Crisitan_grupa_313_CC.(README)pdf		Ion_Andrei_Crisitan_grupa_313_CC.(README)pdf
brand_encoder.pkl		brand_encoder.pkl
erori_reziduale.png		erori_reziduale.png
interfata_grafica.py		interfata_grafica.py
main.py		main.py
requirements.txt		requirements.txt
test.csv		test.csv
train.csv		train.csv

About

A machine learning project to predict product return amounts based on brand, sales, advertising spend, and order data. Includes data preprocessing, exploratory data analysis (EDA), feature encoding, scaling, model training with Random Forest, evaluation, and saving the trained model for future predictions.