Atiqur Rahman

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FleetPulse

FleetPulse is a data visualization tool designed to help companies reduce carbon emissions for their truck and vehicle fleets.

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Technologies: Next.js, TypeScript, Tailwind, Cloudflare, Databricks, AWS, Clerk
Waste.0

Waste.0 is a web app designed to reduce food waste by using machine learning to predict optimal inventory levels and forecast item spoilage, minimizing surplus and waste.

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Technologies: Next.js, TypeScript, Tailwind, MongoDB, Databricks, AWS, Streamlit, Clerk
LegalAI

LegalAI is an AI platform that simplifies legal document review by summarizing contracts, spotting risks, and offering key insights with advanced language models.

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Technologies: Next.js, TypeScript, Tailwind, MongoDB, PropelAuth, UploadThing, Open AI
MavGrades

MavGrades is a platform that provides grade distributions for UTA courses and professors, helping students make informed class choices.

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Technologies: Next.js, TypeScript, Tailwind CSS, SQLite
trasva.com

A travel social platform where users can share their journeys, discover new experiences, and connect with a like-minded community.

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Technologies: Next.js, TypeScript, Tailwind CSS, MongoDB, Clerk
Service Request System

An Android application developed with Java that enables users to place service requests to selected service providers.

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Technologies: Java, Android Studio, Firebase
UTA Datathon 2024 Website

Official website of UTA Datathon 2024 for registrations and general information.

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Technologies: Next.js, TypeScript, Tailwind CSS, Firebase, Vercel
Goblin

A robust expense management web app built with .NET, designed to streamline tracking, managing, and analyzing your financial transactions effortlessly.

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Technologies: C#, .NET, SQL, Azure, Docker
ACM UTA Website

Official website of Association for Computing Machinery (ACM) @ UTA.

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Technologies: Next.js, TypeScript, Tailwind CSS, Firebase Firestore
Credit Card Fraud Detection

Exploratory data analysis and prediction model for credit card fraud detection.

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Technologies: Python, Pandas, Scikit-Learn
CBRE Asset Management

A machine learning model that predicts the maintenance needs in commercial building assets.

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Technologies: Python, Random Forest, K-means

Github Contributions

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