📈Forecasting Total amount of Products using time-series dataset consisting of daily sales data provided by one of the largest Russian software firms📆
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Updated
Jul 23, 2020 - Jupyter Notebook
📈Forecasting Total amount of Products using time-series dataset consisting of daily sales data provided by one of the largest Russian software firms📆
You are opening a new Store at a particular location. Now, Given the Store Location, Area, Size and other params. Predict the overall revenue/Sale generation of the Store.
Digikala data science competition
Predicting the sales of a store
Sales revenue prediction
Deep Exploratory Data Analysis and purchase prediction modelling for the Starbucks Rewards Program data.
This time I am doing it using R language. let's see the results. The solutions includes eda(exploratory data analysis), data visualizations, modelling with Machine learning Models such as XgBoost and AdaBooost etc and check the performance using rmse metrics etc to compare the results.
grocery store sales prediction using neural nets
Bigmart Sales Analysis prediction of the sales, data set from https://datahack.analyticsvidhya.com/contest/practice-problem-big-mart-sales-iii/
Predicting purchase amount in Black Friday dataset. (MAE = 2195)
This Repository is the official project space of team ALMA2020 - Mishmash Online Hackathon.
Linking a pre-existing R Project with GitHub. The project - Predicting Ice Cream Sales - was carried out on 'Statistics with R' module during the MSc Data Science for Business at the University of Stirling.
In this repository, I have done simple python projects for understanding the python environment.
Bigmart Sales Prediction
Pharmalytics is a sales prediction application for Firstmed Pharmacy using the SARIMA model and Streamlit.
RetailRevolutioner, aims to provide a solution to the problem of accurately predicting consumer behavior in the retail industry. Our web application will analyze past sales data from clients to provide accurate predictions of which items will be the most popular in the coming month
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