adi5krish

2-Player-Chess-Game

Developed a fully functionable two-player chess game in Java with the application of OOPs concepts

Balanced-Datasets-Are-Not-Enough

[ICCV 2019] Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations

BHASH

Successfully defined language constructs and completed the syntax analysis for the language we created. Semantic analysis was done for a fair number of constructs using which we can program.

Cancer-Detection-using-CNN

Trained a Convolutional Neural Network to classify breast cancer as Malignant or Benign

CS-for-background-subtraction

Developed a method to directly recover background images from video using Compressive Sensing

Deep-Learning-Python-Notebooks

Deep Learning Python Notebooks

IIITV-Ecampus

Ecampus platform for IIIT Vadodara students, teachers and administration.

Question-Answering-Tool-for-CliCR-Dataset

Question Answering tool for CliCR dataset developed using BERT and BioBERT

Real-Time-Face-Swapping-Tool-using-Deepfake-Algorithm

Implemented a cloud-based real-time face-swapping tool to swap faces in a video. Used CNN auto-encoder based deepfake algorithm and Google Cloud Platform (GCP) based services - Google App Engine (GAE), Google AI Platform for efficient deployment on cloud

Real-Time-Object-Detection-using-Cloud-and-Edge-Computing

Developed an application that provides real-time object detection utilizing both cloud (using AWS) and edge (using Raspberry Pi)

adi5krish/Real-Time-Face-Swapping-Tool-using-Deepfake-Algorithm

Implemented a cloud-based real-time face-swapping tool to swap faces in a video. Used CNN auto-encoder based deepfake algorithm and Google Cloud Platform (GCP) based services - Google App Engine (GAE), Google AI Platform for efficient deployment on cloud

adi5krish/Cancer-Detection-using-CNN

Trained a Convolutional Neural Network to classify breast cancer as Malignant or Benign

adi5krish/Deep-Learning-Python-Notebooks

Deep Learning Python Notebooks

adi5krish/BHASH

Successfully defined language constructs and completed the syntax analysis for the language we created. Semantic analysis was done for a fair number of constructs using which we can program.

adi5krish/CS-for-background-subtraction

Developed a method to directly recover background images from video using Compressive Sensing

adi5krish/Question-Answering-Tool-for-CliCR-Dataset

Question Answering tool for CliCR dataset developed using BERT and BioBERT

adi5krish/2-Player-Chess-Game

Developed a fully functionable two-player chess game in Java with the application of OOPs concepts

adi5krish/Balanced-Datasets-Are-Not-Enough

[ICCV 2019] Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations

adi5krish/Ecampus

Ecampus for IIITV

adi5krish/IIITV-Ecampus

Ecampus platform for IIIT Vadodara students, teachers and administration.

adi5krish/Machine-Learning

This repository contains all the codes for the Machine Learning Course offered in Autumn 2018.

adi5krish/Real-Time-Object-Detection-using-Cloud-and-Edge-Computing

Developed an application that provides real-time object detection utilizing both cloud (using AWS) and edge (using Raspberry Pi)

adi5krish/clicr

Machine reading comprehension on clinical case reports

adi5krish/Designing-CHOMP-game-using-Reinforcement-Learning

Designed a game named “CHOMP” with use of reinforcement learning. Code was made in Python using a renowned algorithm namely “Monte Carlo Tree Search”. Outperformed humans after playing a fair number of games.

adi5krish/frontend-nanodegree-resume

This repository is used for one of the projects in Udacity's Front-End Web Developer Nanodegree program. Learn how to become a Front-End Developer today with line-by-line code reviewed projects and get a job with career services!

adi5krish/grokking-the-object-oriented-design-interview

adi5krish/hello-world

my first repository

adi5krish/react-movie-app

React App designed with the MERN stack

adi5krish/Statistical-Machine-Learning

This repository contains the codes for the assignments given in Statistical Machine Learning course offered in FALL 2019