design and implement a machine learning model which predicts daily sales count of each product
سه سال پیش منتشر شده
تعداد بازدید: 418
کد پروژه: 232906
شرح پروژه
The 60 days sales history data of about 5000products have been proposed (Train Dataset).
As it is explained in the table, the data contains 29 columns. One of the classic problems of retail
businesses is to predict the future daily sales for each product.
You are asked to design and implement a machine learning model which predicts the next 30 days'
daily sales count of each product for Amazing, promotion, and Normal sales based on the previous 30
days' sales history data. Also, we want you to predict two warehouses share coefficient which specifies
each warehouse sales count. (Predict red cells)
As the final answer, you have to run your model for about 2040 products (Test Dataset) to predict
their next 30 days daily sales count (Amazing, promotion, Normal) and the warehouse's share
coefficient based on their previous 30 days sales history data. Your final answer should be a CSV file
مهارت ها و تخصص های مورد نیاز
بودجه
5,000 تومان تا 100,000 تومان
مهلت برای انجام
10روز
وضعیت مناقصه
بسته
درباره کارفرما
عضویت هفت سال پیش
