TAMU Datathon 2023: build your analytical skill set and create data-driven solutions in 24 hours. WITH data science lectures, workshops, challenges, prizes, fun activities, swag, food, and more! - Devpost

Soil Texture Classification: A Modern Approach Comparison — Soil Texture Classification: A Modern Approach Comparison

A lower-cost, small and fast model that provides similar accuracy to previous papers. Tailored ideal for uploading or completely running on mobile devices pre-trained.

TD Hospital Exploration — TD Hospital Exploration

Using LightGBM, we streamlined data to predict patient survival accurately, prioritizing key features and ensuring model reliability."

Are You Gonna Die? — Are You Gonna Die?

Using hospital data and stats, Are You Gonna Die gives insight into cutting-edge technology, accurately predicting if a patient has a chance of life. Our model outpaces doctors giving fast results.

Team 7 | Marky Social Media Post Approval Prediction — Team 7 | Marky Social Media Post Approval Prediction

Providing key insights for success on social media platforms.

Beginner Challenge — Beginner Challenge

Have you ever wanted some random TAMU freshman to debug some data science code? Well now you can!

Pic Predict — Pic Predict

Pictionary Plunge - Where Art Meets AI! Our 2M Parameter CNN will astound you as it effortlessly guesses your sketches, making every game a thrilling challenge.

Patient Survival Predictive Analysis — Patient Survival Predictive Analysis

Our project predicts patient survival using data cleaning, standardization, and oversampling. It is also adaptable, allowing for the use of different machine learning techniques.

Medical Data Cleanser — Medical Data Cleanser

We help decide people's fate based on our machine learning algorithm and squeaky clean dataset. Put your fate in our hands, it isn't a gamble...

TD Hospital Exploration — TD Hospital Exploration

We utilize data from a hospital's patients and predict the survivability chance of new patients through a multi modal model of machine learning comprised of logistic regression and neural networks.

Optimizing model using multiple methods — Optimizing model using multiple methods

Enhanced Model Performance: A Data Preprocessing Journey

we KNOW what you are drawing — we KNOW what you are drawing

We will guess every single thought of you when you are drawing!

RaceBots — RaceBots

Algorithmic approach to solving racebots problem.

TD Hospital Exploration Challenge — TD Hospital Exploration Challenge

We were provided a sample dataset that contained different medical factors of patients. We had to clean the data of any improper values and correlate which factors led to death most often.

Pictionary Plunge — Pictionary Plunge

An LSTM based predictor

Marky Post Approval Classification Project — Marky Post Approval Classification Project

Determining how likely a user is to approve generated posts is helpful in improving Marky's product. Using predictive modeling and machine learning algorithms, our project does just that!

Pictionary Plunger Challenge — Pictionary Plunger Challenge

As a person makes strokes for a drawing, our machine learning model will make classifications and predictions on what that person is drawing!

Increasing Our Sustainability Awareness — Increasing Our Sustainability Awareness

Data Unlocked: Shaping a Sustainable Tomorrow

TD Hospital Exploration — TD Hospital Exploration

Unlocking Insights for Better Healthcare at TD Hospital

Texas A&M Bus Routes Dataset — Texas A&M Bus Routes Dataset

Frustrated because the bus is never on time during rush hours? This dataset contains the location data for multiple routes scraped frequently which can be used to predict bus arrival times.

TAMU Datathon 23 — TAMU Datathon 23

I utilized graphs and Google Sheets to determine that cancer and age are relevant indicators of mortality

TD HOSPITLA — TD HOSPITLA

This works to find the best features to help predict death rate across unseen data.

Sadness — Sadness

Goal of this code is to take the hospital dataset and clean the values that are not helpful. Then it uses PCA to simplify data. Then it uses linear regression to predict outputs for a given input.

MarkyChallenge — MarkyChallenge

Discover the secrets behind AI-generated content approval in our report. We've delved into the language, tone, and engagement factors that matter most.

Social Media Post Approval Prediction with Marky — Social Media Post Approval Prediction with Marky

Our team aimed to unravel the hidden insights within the dataset, ultimately delivering a predictive solution that helps streamline the post approval process for social media content.

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