Benchmark for Burk et al. (2024)

By integrating geographical data analysis and statistical modeling, CTCA aims to inform strategies for reducing crash rates and enhancing road safety. This initiative combines innovative data processing techniques with advanced analytics to offer actionable recommendations for policymakers, urban planners, and public safety organizations.

Analyzing housing complaints in New-York-City and develop a forecasting model

Python programming labs done throughout the course CSC406 - Artificial Intelligence

Marketing strategies on the sales volume and average retail price (ARP) of Good Belly products. Using a dataset encompassing sales, promotions, and demographic information across multiple regions, this project employs causal analysis and multiple linear regression to provide insights into the effectiveness of marketing activities.

client subsection to a term deposit

Analyzing and classifying French tweets related to global warming and drought using NLP and Machine Learning. - Analyse et classification des tweets français parlant du réchauffement climatique et de la sécheresse en utilisant le traitement du langage naturel (NLP) et l'apprentissage automatique.

Text Processing RNN leverages RNN and LSTM models for advanced text processing. It features deep learning techniques for NLP tasks, utilizing GloVe for word embeddings, aimed at both educational and practical applications.

Prediction of happy Customers based on Happiness Survey Data