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
Comparing power producers in US and ranking them
This is an analysis of the predictors in the Binghamton housing prices data
we are intended to estimate and analyze house price, and also compare the houseprices of different distance.
1)Developing "Random Tree" ML algorithm by ourselves; 2) Manage to train and get the prediction model.
The old model was bad and was losing us money. The new model is more efficient and will make us money
A song written from the most popular lyrics of other songs
Analysis on dataset and prediction
We analyzed the pharmaceutical data sponsored by RxRefund to determine the most effective AWP price for a product.
Using 7 features extracted and cleansed from Political Science Dataset, machine learning predicts outcome of protest
Machine learning algorithms that will allow you to predict housing prices accurately
Properties
its not clickbait. its real life.
Analysis of factors of protest and re-revolt
Price prediction and business recommendation
Here's the dirty python notebook for my project
1 – 15 of 15