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No longer have to BEAR the long lines for advising!
GoodWork is a push for pursuing exercise through volunteer service over working out at the gym. We strive to empower others with the desire to maximize the good they can do for their own communities.
Effectively being present in a lecture when you physically cannot be there is a challenge that our team wanted to take on. Schola effectively emulates being physically in class in the digital sphere.
Parenting is hard. Sentimetica makes your job of being a parent a bit easier. Sentimetica is a service that lets parents know if their child is emerged in a negative ecosystem on YouTube.
Predicts how many tweets someone will have in the next week based on previous weeks.
This project combines data scraped from twitter.com and airlinequality.com to determine user sentiment using machine learning
Helping small eating spaces to keep up with competitor in the market. by making the Intelligent decisions using ML& analytics for marketing as well as to find a best way to please the customer
Lightbulb Companion is an extension to NCR's Silver API. Since existing solutions only analysed historical data, we set out to create a dashboard that provides management with predictive insights.
Machine learning is one of the most prominent categories in the ever advancing field of technology, and we wanted to make the implementation an easier process for everyone.
A tiny quantum-circuit duel!
A Basic Approach to the 2d Bin Packing Problem
A Daily Sentiment of Everything
My project builds and trains a neural network to recognize and classify alphanumeric characters and then extract text from images labeling objects in the image
Mdoc uses AI in a privacy preserving manner to predict how likely Bob is likely to sign this document
autonomous system for hate speech moderation for an inclusive work-space
Optimizing Treatment for Parkinson's Disease
An AR-based, offline solution for emergency professionals to administer the accurate dose of medication to pediatric patients
In this project, we will investigate utility of Prewitt-Sobel hybrid edge detection methods upon certain gastrointestinal specimens.
We are trying to build a classifier mode to predict down hole failures based on sensor information
A machine learning logistic regression model for classification that predicts stripper oil well failures as either occurring down-hole or surface-level with 99% accuracy
Use spatial binning for image retrieval and application of image processing to solve shortest path problem
We are given a set of data about machine failures, we are able to predict future failures.
Our self-sustaining model helps to understand "location preferences" of opening a taco/burrito restaurant in the United States of America.
Looking at where the authentic tacos/burritos are in the U.S.
