Python ML #08: Sales Forecast Tutorial with Linear Regression Model #machinelearning #coding #python
In this machine learning tutorial, you will learn how to forecast sales and compare actual and forecasted sales using different metrics such as mean squared error, mean absolute error and R2 score using Linear Regression model.
We are going to use sales data from different stores from 2013 to 2017
[ items sold per day ].
***Google Collab*** is being used in this tutorial instead of VS Code.
✨Download the dataset file : https://github.com/BekBrace/Sales-Forecast-data-csv
🔗 Social Media
--------------------------
Facebook : https://www.facebook.com/bekbrace
Twitter : https://twitter.com/BekBrace
Instagram : https://www.instagram.com/bek_brace/
Tech Blog : ttps://dev.to/bekbrace
GitHub profile : https://github.com/BekBrace
Website : https://bekbrace.com
Join this channel to get access to perks:
https://www.youtube.com/channel/UC7EVSn5inapL20oPSwAwEUg/join
In this machine learning tutorial, you will learn how to forecast sales and compare actual and forecasted sales using different metrics such as mean squared error, mean absolute error and R2 score using Linear Regression model.
We are going to use sales data from different stores from 2013 to 2017
[ items sold per day ].
***Google Collab*** is being used in this tutorial instead of VS Code.
✨Download the dataset file : https://github.com/BekBrace/Sales-Forecast-data-csv
🔗 Social Media
————————–
Facebook : https://www.facebook.com/bekbrace
Twitter : https://twitter.com/BekBrace
Instagram : https://www.instagram.com/bek_brace/
Tech Blog : ttps://dev.to/bekbrace
GitHub profile : https://github.com/BekBrace
Website : https://bekbrace.com
Join this channel to get access to perks:
https://www.youtube.com/channel/UC7EVSn5inapL20oPSwAwEUg/join
