Predict how much GStore customers will spend

Movie Revenue & Ratings Prediction Using 5000 IMDB Movies [Python, Machine Learning, GitHub]

Kaggle competition of Google Analytics Customer Revenue Prediction

In this project, We have created a model which will predict the revenue in dollars.

Forecast of advertisement revenue for the coming months and reserved price prediction for bidding price.

In this project, I applied Linear Regression model to solve the task using python

Design a predictive model identifying users likely to subcribe or not allowing to focus marketing ressources to increase conversion

Predicting the Advertisement Revenue for a auction website along with setting the range of bidding values for next auctions.

The inventory system simulates the stocking level and the revenue of Cantilever Umbrellas in an Australian firm.

CLV prediction using Regression Analysis of customer invoice data for an online retail store

Solution to the "Google Analytics Customer Revenue Prediction" Kaggle Competition

You can find a fictive business case for a linear regression

Utilizing facebook-prophet machine learning model to analyze MercadoLibre's financial and user data to identify search traffic trends and predict stock prices and sales revenue.

A workflow that estimates Airbnb pricing and predict the rental properties annual revenue based on the characteristics of the Airbnb.

A demonstration of advanced graphing techniques, table usage, and advanced array formulae usage in Excel.

This report analyzed KPIs to assess Whole Foods' financial health and performance. It benchmarked the peer retailers, revealing critical success factors and each business model's strengths and weaknesses. A regression model forecasted Whole Foods' revenue growth, and CAPM estimated the future stock trend to provide recommendations to shareholders.

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.

This repository uses a Kaggle dataset for a classification task: determining if bank clients are likely to invest in long-term deposits. Aimed at assisting banks with revenue declines, it targets customer classification, optimizing marketing efforts towards potential long-term depositors.