Hello!
I'm Arnav Deep, a software engineer focused on building solutions for billions.
Get in touch arnavd4@gmail.com
I completed my B. Tech. graduation in Computer Science and Engineering from IIITDM Jabalpur. I have worked and developed many features and products in various segments for different companies.
As a software engineer, I enjoy bridging the gap between code and applications — combining my technical knowledge with my meticulous intellect for problem solving to create a beautiful product. My goal is to build applications and provide solutions that are efficient under the hood and scalable for billions while providing engaging enhanced user experience and life.
When I'm not in front of a computer screen, I'm probably playing board games, reading a book, binge-watching or crossing off another item on my bucket list.
- C/C++
- Rust
- Python
- Java
- HTML
- CSS
- JavaScript
- SQL
- Django
- Android Framework
- React
- Node
- Flutter
- WordPress
- Flask
- Data Structures
- Algorithms
- OOPs
- Machine Learning
- Deep Learning
- Rest API
- Bash
- Git
- MongoDB
- Azure
- AWS
A topic modelling Suggestion model that recommedns movies based on their plots. Dataset of over 35,000 movie plots have been used. Working of the Python script can be seen here.
Develop an IoT based system to detect leopards using Custom Object Detection from live video feed and an Android app for alerting the authorities.
A Custom Object Detection using YOLOv3 to detect leopards from live video feed built as part of engineering design project.
A generalised Topic Modelling tool using Latent Dirichlet Allocation (LDA) model ready to be used for any English dataset.
An app to perform CRUD on Firebase database using SMS as a trigger.
An android app connected to an Arduino based IoT system for the security of children to get their current location, pulse rate and temperature.
Gaussian and Binomial Distribution Python package available on Pypi, ready to be installed with pip.
An Android app to find grocery in some cities using data from Google by Places API.
A Deep Learning model using Convolutional Neural Network for American Sign Language (ASL) with 98.5% accuracy.
An Image Processing tool to Estimate Building Height from Shadow of a building in a VHR Satellite image implemented from the IEEE Paper A Shadow-Overlapping Algorithm for Estimating Building Heights From VHR Satellite Images.