Data-driven Decision Making project to predict location of oil and petroleum refineries in United States

Python code that predicts which course a student will register for based on their previous registration history.

Describes Bixal's development methodology

Program Description and Certificates for the MicroMasters Program in Business Analytics

Minimize the risks and maximize the benefits of using data-driven technologies within government processes, programs and services through transparency. | Réduire les risques et à maximiser les avantages liés à l’utilisation de technologies axées sur les données, dans le cadre de processus, programmes et services gouvernementaux, grâce à la trans…

Alpha principles for the ethical use of AI and Data Driven Technologies in Ontario | Proposition de principes pour une utilisation éthique des technologies axées sur les données en Ontario

MPS Analytics Coursework [2020 - 2021]

Google Data Analytics Professional Certificate

Code for the Journal of Cleaner Production paper: Data-driven Assessment of Room Air Conditioner Efficiency for Saving Energy (https://doi.org/10.1016/j.jclepro.2022.130615).

Hybrid Deep MILP Planner (HD-MILP-Plan)

My repository for the Data-Driven Decision Making Program at I2A2

Built a classification model to predict clients who are likely to default on their loans. With the challenge of a limited dataset was able to build and tune a Random Forest Model maximized for a recall score of 80%. Significant EDA and feature analysis were done to identify key features and make business recommendations moving forward.

A critical problem in EdTech is converting potential customers into paid customers. Performed EDA to identify the key factors driving the lead conversion process and built an ML model (using Decision Trees and Random Forest) that identifies which leads are more likely to convert.

Built a linear regression model to predict house prices in Boston. The final model is generalized and perfectly predicts prices with a 100% r-squared. Significant EDA and feature analysis were done to identify key features and make business recommendations moving forward.

BeNeutral helps people save money and the environment by making their homes energy-efficient. We calculate co2 emitted by a house, advise how to reduce it and encourage to offset the rest by planting trees. The goal is for a household to achieve and maintain carbon-neutrality.

Unleashed the power of data science to analyze the performance of golfers from the PGA tour. Built ML models and compared Strokes Gained to traditional metrics, resulting in insightful findings and actionable recommendations for golfers at all levels. Showcased advanced data analysis, decision trees, and visualizations in this comprehensive project

Analyzing Retail data to explore the dataset and answer a main question which is how we can make more money by improving weak areas and represent the data in an interactive way.

Visual analysis application for the data collected by a Formula Student car during driving, aiming to evaluate and compare the drivers of the team.

Recipe Site Traffic Prediction: Utilising machine learning to forecast high traffic recipes on a recipe website. Improve user engagement and traffic with data-driven decisions.

A predictive model for postgraduate program enrollment based on historical data, student rankings, and various influencing factors.