Abstract

This project explores the problem of predicting gym class attendance using machine learning models. The dataset used in this notebook contains information about gym members such as their months as a member, weight, days before booking, day of the week, time of the day, and category of the class. The goal of this notebook is to predict if a gym member will not attend the class so that the gym can make another space available for other members. 

Two machine learning models, Decision Tree and K-Nearest Neighbors (KNN), were trained and evaluated using precision and specificity as the priority evaluation metrics. The KNN model performed better compared to the Decision Tree model in this problem, gaining the highest score in the two priority evaluation metrics stated above. 

The notebook also includes data exploration, data preprocessing, and visualization of the results. Overall, this notebook provides insights into how machine learning can be used to predict gym class attendance and help gym management make informed decisions.

Abstract

This analysis aims to determine the most effective sales strategy for driving revenue growth in the office stationery line of Pens and Printers. The three sales strategies implemented were targeted email campaigns, personalized phone calls, and a combination of both. The objective is to identify the sales method that has been the most successful in driving revenue growth by comparing the revenue data over the past six weeks since the product launch. The business metric used to measure effectiveness is the Revenue Growth Rate, which calculates the percentage change in revenue from one period to another. The baseline revenue from the first week is used for comparison, and the performance of each sales method is observed to assess their impact on revenue growth.

Abstract

In the dynamic landscape of 2022, Trinity Road established partnerships with over 30 vendors, united under the values of Truth, Goodness, and Beauty. Driven by a commitment to deliver exceptional products and services that honor the community and uphold spiritual principles, Trinity Road embarked on a comprehensive analysis of vendor performance throughout the year. The primary objective of this endeavor is to ascertain the financial performance of Trinity Road in 2022. Accompanied by secondary goals, this analysis aims to illuminate key insights into drop ship financial performance, compare vendor contributions, and delve into specific vendor performance details. This initiative is geared towards enhancing understanding and optimizing outcomes, contributing to Trinity Road's continued growth and success.