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
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Updated
Jun 23, 2021
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
Hybrid Deep MILP Planner (HD-MILP-Plan)
SOMOSPIE (Soil Moisture Spatial Inference Engine) consists of a Jupyter Notebook and a suite of machine learning methods to process inputs of available coarse-grained soil moisture data at its native spatial resolution. Features include the selection of a geographic region of interest, prediction of missing values across the entire region of int…
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…
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
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).
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.
Program Description and Certificates for the MicroMasters Program in Business Analytics
A predictive model for postgraduate program enrollment based on historical data, student rankings, and various influencing factors.
This project involved analyzing AdventureWorks bike sales data to uncover key insights into sales performance by country, customer segments, and products. The findings informed strategies for targeted marketing, market expansion, promotional timing, and product quality improvements.
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.
Scraping LeetCode data, analyzing for insights, crafting a user-friendly dashboard, and building a problem recommender for optimized problem-solving.
The project dives into transaction records of an online retail business to uncover hidden relationships between products. The overall goal is a data-driven approach to enhance the customer shopping experience, improve loyalty, boost profitability, tailor marketing strategies, and optimize inventory management via strategic business decisions.
Visual analysis application for the data collected by a Formula Student car during driving, aiming to evaluate and compare the drivers of the team.
Enhancing Airline Performance Analysis for the Department of Transport
Streamlined digital library management system for cataloging, lending, and user access.... Created at https://coslynx.com
This Project aims to analyze the performance of Employees in lead generation activities.
Data-driven Decision Making project to predict location of oil and petroleum refineries in United States
MPS Analytics Coursework [2020 - 2021]
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