emilbiju

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.

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

emil-risc-v

32 bit RISC-V CPU implementation in Verilog

emilbiju

emilbiju-website2

emilbiju.github.io

Personal website

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.

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.

emilbiju/emil-risc-v

32 bit RISC-V CPU implementation in Verilog

emilbiju/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.

emilbiju/Ad-Click-Prediction

Machine learning models to improve AUC scores in large-scale, highly skewed datasets.

emilbiju/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.

emilbiju/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.

emilbiju/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

emilbiju/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/emilbiju

emilbiju/emilbiju-website2

emilbiju/emilbiju.github.io

Personal website

emilbiju/hiring2020

Internship status of companies - COVID-19

emilbiju/Image_resolution_enhancement

A Convolutional Neural Network based model for enhancing image resolution

emilbiju/just-the-docs-test

A modern, high customizable, responsive Jekyll theme for documention with built-in search.

emilbiju/MaxScatterTSP

Perturbation Analysis of Practical Algorithms for the Maximum Scatter Travelling Salesman Problem @ ALENEX '22

emilbiju/quora-qpairs

Approaches to the Quora Question Pairs Task

emilbiju/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.

emilbiju/Tutorials

Tutorials for creating figures, tables, or other content for AAS Journals.

emilbiju/xarray

N-D labeled arrays and datasets in Python