📈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

This project focuses on time series forecasting to predict store sales for Corporation Favorita, a large Ecuadorian-based grocery retailer. The goal is to build a model that accurately predicts the unit sales for thousands of items sold at different Favorita stores.

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 contains the tasks for data science internship at codsoft

This Repository is the official project space of team ALMA2020 - Mishmash Online Hackathon.

In this repository, I have done simple python projects for understanding the python environment.

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.

Sales Price Prediction is a data-driven approach that utilizes machine learning algorithms to forecast product prices accurately. By analyzing historical sales data and other relevant features, it helps businesses make informed decisions, optimize pricing strategies, and predict future sales trends, enhancing overall profitability.