This project is an expanded version of a machine learning model used for my WGU capstone project.

Capstone project for Western Governor's University B.S. - Computer Science program

Predictive modelling for customer conversion and transaction revenue at Google's e-commerce shop

Predicting youtube revenue using ML models

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.

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 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.

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

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

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.

You can find a fictive business case for a linear regression

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

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

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

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

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

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

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