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Identifying trends and relationship between Pneumonia, COVID, and influenza deaths and flight travel by state in the US from 2020-2021.
Flysight integrates multiple datasources to derive insights into growing profitability of airlines, utilizing machine learning, airport geodata, flight info, and Bloomberg projections.
Understanding the variables that correlate and can be useful in help predicting airline demands
Does the location of a restaurant relative to a transportation stop affect its review count or rating?
Charting New Heights: Optimizing Crew Scheduling
Built a website displaying our findings and interactive data graphs.
Our travel itinerary service combats popularity bias in traditional recommendations, helping adventurous travelers discover hidden gems and support small local businesses while avoiding tourist traps.
A trend that uncovers information that improves retail businesses.
How do mortality trends in pneumonia, influenza, and COVID-19 differ across regions of the United States, and what insights can be gained in relation to flight cancellations during the pandemic?
Trying to find the correlation between the months and the deaths caused by Influenca, Pneumonia, and COVID-19.
Using a machine learning model (neural network) we are able to predict the costs of flights.
Which countries and/or companies from specific countries should engage in carbon trading? Have policies like the Carbon Offsetting and Reduction Scheme for International Aviation worked?
Exploring CO2 Emissions with different variables
Analyzing at a data set from Kaggle, we looked at factors such as average fare, distance, and destination that could have possibly affected passenger volumes on flights between 1993 and 2024.
Our project aims to investigate the nuanced relationship between aviation CO2 emissions, tourism, and GDP across different nations.
State of the art personalized tourist attraction recommender by leveraging RAG despite Tourpedia's not so reliable API.
Harnessing Data Science to Forecast Aviation CO2 Emissions and Drive Global Policy Change
How did travel before, during, and after the COVID-19 pandemic relate to death rates in the US for airborne diseases?
This repository contains a Python implementation of a Decision Tree Classifier to categorize the 'large_ms' variable into three distinct groups: 'Low', 'Medium', and 'High'.
Considerations for the next outbreak.
How have different countries' airline CO2 emissions changed overtime?
Analysis of airline travel trends by HHS region during COVID using Excel, Rstudio, and Python.
Identify MOST Cost-Effective Carrier Based on Personalized Journeys
We’ve organized attraction data points into a user-friendly resource with an interactive map, helping users easily find London attractions.
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