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Sales Prediction Using ML

In this project, we'll develop a machine learning model that forecasts a company's sales based on investments in various forms of advertising.

Detailed overview

Every business uses its unique advertising methods, but spending too much money on them doesn't boost sales. For instance, investing in newspapers no longer results in more sales. Therefore, we must determine which form of advertising generates the most sales.

I have chosen a dataset of a company. The investments and sales for the preceding 10 years are divided into columns in this dataset.

Now, i created a machine learning model using 3 different algorithms. They are,

  1. Linear Regression
  2. Random forest
  3. Decision Tree

models.py file has the code for different algorithms. graphs.py file has the code for creating the graphs. model.pkl is the trained ML model sales_ir, sales_rfr are the final codes of the project

Deployment

To deploy this project on heroku follow the steps:

  1. Download this code from github.
  2. app.py has the final code for deployment and index.html is the code for web page.

Author

Sudhan Jee