Hena Shah

Growing out of the comfort zone

Designed a model for image classification which improves the learning behavior of Residual Networks and has better accuracy  compared to previously published state-of-the-art models with 5.62% error rate, least in existing models
The preprint arXiv paper has been cited 10 times and received appreciation from Node.js founder, Ryan Dahl via Twitter
Publication: ACM Digital Library ISBN 978-1-4503-4301-5

Deep Residual Network using Exponential Linear Unit

Implemented IJCA 2015 paper research using Textblob to classify tweets into positive, negative and neutral sentiment in Python

Tweet Sentiment Classification

Data Visualization of Indian Elections

Scheduling College Department Hall

Accomplishments / Portfolio

Publications

Python

Java

Algorithm

Machine Learning