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Predicting oil production at Chevron wells.
Unlocking the Future of Energy Production: Predicting Peak Oil Production with Historical Renewable Investments Data using a StackingRegressor with an RMSE of 97.35.
Automate sleep stage classification, using multivariate physiological signals​ with ensembled Multivariate Time Series Classification(ResNet) and Time-Series Segmentation(U-net) models
Machine Learning the Path to a Restful Tomorrow. Our project implements sleep stage classification with an 89.6% accuracy given neurological and physiological data.
Uncovering Product Dangers and Offering Regulatory Guidance
In this project, we aim to analyze the FDA report data, identify potentially dangerous consumer products and patterns, and then provide recommended regulatory actions for FDA.
Evaluate how a MLB team's winning odds are impact by recent travel history using logistic regression, adjusted for baseline skill computed via Elo rating.
We used innovative data cleaning and feature engineering methods to turn an incomplete dataset into an excellent one. We developed a random forest model for accurate prediction and feature selection.
How does an MLB team's schedule effect game performance?
Using Python and R to analyze CAERS data for trends to provide regulatory recommendations for the FDA
This project is on the Beginner's Track for the Rice Datathon, created by the team Cluster Busters consisting of Andrew Holzbach, Melody Jing, Meaghan Ramlakhan, and Pinar Targil.
We used OPS+ to determine the effects of travel on aggregate team offensive performance.
Sleep is powerful! It makes or breaks job performance, education, and disproportionately affects low income areas. We uncover the secrets of sleep stages with frequency power analysis of EEG data.
Chevron Track
We knew nothing about Python and data science before this competition, and Datathon provide us with an opportunity to learn so much! Thank you to all the organizers and the mentors in Rice Datathon.
The Gaussian Curveballs hit a grand slam with their work investigating the relationship between MLB team travel and performance.
We engineered a new feature to easily analyze the severity of the medical conditions after using the product
Serving out clean and spicy data!
Guiding You Through the Mysteries of Sleep
Chevron Project
Rice Datathon 2024 Chevron Track
Analyzing the adverse event data to identify potentially dangerous consumer products and patterns, and providing recommended regulatory actions to the FDA.
Empowering Oil Futures: Precision Peak Rate Prediction for Informed Well Development
-Predict Peak Oil Rate
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