Devpost
Participate in our public hackathons
Devpost for Teams
Access your company's private hackathons
Grow your developer ecosystem and promote your platform
Drive innovation, collaboration, and retention within your organization
By use case
Blog
Insights into hackathon planning and participation
Customer stories
Inspiration from peers and other industry leaders
Planning guides
Best practices for planning online and in-person hackathons
Webinars & events
Upcoming events and on-demand recordings
Help desk
Common questions and support documentation
We analyze how the count of wildfires and its consequences have changed over time as a function of climate change, and its indications for our climate and health.
This is our analysis of the Storm Events across the United States, with a focus on the damage caused by calamities in the Tornado Alley
The Relationship Between Political Affiliation & Greenhouse Gas Emissions in Counties Across the U.S.
Analyzing Green House Gas emissions and how they relate to industry sector.
This project identifies major contributors to the flood health crisis of San Francisco and suggests mitigation strategies for improving housing equity and access to healthcare services.
Given the dataset of SF Flood Health vulnerability, our team worked together to utilize data to find the best approach for a flood response for high risk areas.
How have people's attitudes towards our climate changed over recent years?
#natural_science_track #greenhouse_gas #climate_injustice
CDC entry for Natural Science Track
Using Principle Component Analysis to improve the Flood Health Index with additional significant variables.
We're examining the relationships between vulnerability to climate change, mental health, and poverty.
Rising emissions have been a growing issue in our modern world. The Covid-19 pandemic has altered these trends in significant ways. We visualize these trends in our presentation.
Analyzing storm data in the U.S. since 1950.
We explored the association global emission changes over the decade, and how they may relate to real-time climate events happening today, such as heat waves.
We created a project that would allow us to predict the number of deaths based on the year, event type, month, and state. We assessed the linear model to see if it would allow us to predict deaths.
Our project predicts the flood vulnerability index based on user adjustable features like elevation, sea level, poverty, and education. It is based on the lightGBM model.
our team uses python to analyze the tweets around climate topics.
Using chosen demographics of San Francisco to analyze and predict health impacts of flooding.
Using a Harvard dataset of climate-related tweets from 2017-2019, we analyzed the impact of these tweets on climate legislation.
Well-informed Data Analysis & Optimal Solution of "Natures Fury"
A web application developed to allow anyone to visualize the data that makes up the San Francisco Flood Health Vulnerability Index by neighborhood.
For our CDC Fall 2022 project, we decided to focus specifically on greenhouse gas direct emissions between the years of 2011 to 2020.
Here we analyze the disparities between minority and economic groups and how they may be more present in flood zone areas within San Fransisco.
null
1 – 24 of 28
