💸 CS498HS4: Computational Advertising in Fall 2018, UIUC
A repository of advertisement prototypes and patterns for testing and development purposes.
Automated video advertisement content analysis system using Sentence Transformers and cosine similarity for yes/no question evaluation. Features text embedding with all-mpnet-base-v2, batch processing, vector indexing, and performance evaluation against human-coded ground truth data.
CSCI576 Final Project. Detecting and Replacing Advertisements in Multimedia Content based on Brand Images/Logos.
This project analyzes advertisement responses using a Django backend and a Vite+React frontend. It includes scripts to load, clean, and transform data, which are executed within Docker containers. Data is stored in a MongoDB database, and the project can be run with or without Docker by adjusting the MongoDB connection strings.
My final project for DACSS 601 (Data Science Fundamentals) titled 'Analyzing Snapchat Political Ads in the US in 2020'
Ad Detector, checks if image is ad-creative or not
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