Emil Biju's repositories
emil-risc-v
32 bit RISC-V CPU implementation in Verilog
Signature_verification_model
This is a Siamese based model for offline signature verification. It utilizes convolutional neural networks and deep learning to compare an original signature sample with a test sample and predict whether the test sample is genuine or forged.
Ad-Click-Prediction
Machine learning models to improve AUC scores in large-scale, highly skewed datasets.
BERT-Paths
This work demonstrates an altogether different utility of attention heads. Self-attention heads are characteristic of Transformer models and have been well studied for interpretability and pruning, but here we build a novel adversarial detection model based on them.
indic-swipe
IndicSwipe is a collection of datasets and neural model architectures for decoding swipe gesture inputs on touch-based Indic language keyboards across 7 languages.
Classification_Wine_Dataset
This is a project aimed at building machine learning models for classification of the wine dataset. Various machine learning models are used and fine-tuned to obtain desirable results for both binary and multi-class classification
CranfieldInformationRetrieval
This repository contains code for an information retrieval system built for the Cranfield dataset as part of the CS6370 course at IIT Madras
emilbiju.github.io
Personal website
hiring2020
Internship status of companies - COVID-19
Image_resolution_enhancement
A Convolutional Neural Network based model for enhancing image resolution
just-the-docs-test
A modern, high customizable, responsive Jekyll theme for documention with built-in search.
MaxScatterTSP
Perturbation Analysis of Practical Algorithms for the Maximum Scatter Travelling Salesman Problem @ ALENEX '22
quora-qpairs
Approaches to the Quora Question Pairs Task
Titanic_survival_challenge
This project is based on the Kaggle challenge called 'Titanic: Machine Learning from Disaster.' It aims to use existing data regarding passengers aboard the Titanic, including their age, gender, cabin class, ticket fare, etc. to build a model that can predict the survival of a passenger from the test set.
Tutorials
Tutorials for creating figures, tables, or other content for AAS Journals.
xarray
N-D labeled arrays and datasets in Python