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OMNY-ANALYST: While others hallucinate, we automate. 12 months of compliance in 10 mins with Gemini 2.0. Scalable. Fast.
For food and retail brands, it can provide real-time insights into customer emotions and cravings which can then help them tailor marketing campaigns.
Rethinking Emoji Prediction with Semantic Understanding
Do you ever wonder if gas prices differ locally? So local, that gas prices could be different in another city right next to you?
Given a tweet with its emoji removed, can a model predict which emoji the author used? This project explores that question by training and comparing three classical machine learning classifiers.
A data-driven predictive tool for marine tracking. We utilize logistic regression and environmental feature engineering to forecast seal sighting likelihoods, visualized on a custom interactive map.
Using 311 service data and American Community Survey data to geographical overlay how service requests are handled in areas of different financial, racial, and educational demographics.
Our AI uses Melissa’s dataset to connect people with ideal communities in Rancho Santa Margarita—matching them with neighbors who share their values and interests.
Can a machine read between the lines of a tweet and pick the right emoji? We trained 5 models to find out and the mistakes were more interesting than the accuracy.
Analyzing the effect different factors, such as HDI and unemployment rate, on depression across seven countries across the globe.
AquaResponse helps firefighters predict fire spread using historical data, locate nearby water sources, and assess risk levels based on elevation, topography, wind levels, and fuel sources.
Busi uses weighted parameters and SQLite3 to calculate business viability scores. By pairing LLM-driven weights with geographic APIs, we pinpoint the ideal spot for your next shop.
Our project predicts housing instability by analyzing price and movement trends, helping users spot high-risk areas before displacement happens.
A data-driven approach to NBA in-game coaching decisions, identifying the key factors that should influence lineup choices in close games.
V.I.P.E.R detects AI-generated images using deep learning + forensic signals like frequency and sensor noise, achieving 96%+ accuracy while explaining every decision.
I built a company health scoring engine that turns complex financial data into a simple 0–100 risk score — so anyone can invest smarter.
Finding important job skills in the Tech world
Because We Just Want A Double Double
Emergency Intelligence System -when every second matters.
#worldcupdatabase
AI powered loan default prediction system with real-time risk scoring, explainability, and what if analysis built on 150,000 real credit records.
a smart parking assistant that predicts the likelihood of receiving a parking ticket based on real citation data.
Wondering whether or not you're fit for a job? Our project allows you to upload your resume as well as the link to a job description to find out whether or not you are fit for the job.
What do emojis play in helping AI determine Sarcasm?
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