Suvrodeep Debnath's Projects
My Personal Blogging app built using React-vite.
Real-time bulk community chatting app powered by React-Next JS, designed with Ant Design, and fueled by Chatengines.io for seamless and engaging group conversations. Join the conversation and connect with your community like never before!
An Integrated video chat cum meeting application. Features are added on weekly basis.
This is my first project on AI - Machine Learning. In this project, I used Pandas, NumPy, Scikit Learn, and Matplotlib as tech-stack. This project basically gives an overview report on Credit card fraud detection.
A React-based web application that provides real-time cryptocurrency data, including prices, market cap, trade volumes, and historical charts. Explore the world of cryptocurrencies and track your favorite coins!
This project is based on AI - Machine Learning. Dataset is visualized by K-Means Clustering in this project.
The Dog vs Cat Identification project is an exciting application of machine learning that aims to accurately classify images of dogs and cats.
A financial optimization overview on Indian agricultural system i.e. practical overview of financial backbone of Agriculture.
An ecommerce application built using React and Tailwind.
Firebase Contact App is a lightweight and user-friendly application built using Firebase's real-time database. It allows users to seamlessly store, manage, and retrieve their contacts, ensuring efficient communication management.
Add your own CSS Animations for any of the component for contribute in this repository
This project can detect heart disease. I used NumPy, Pandas, Seaborn, and SciKit Learn for this project.
Java Spring Boot is a powerful and lightweight framework that simplifies the development of Java applications. It provides a comprehensive set of tools and conventions for building standalone, production-ready Spring applications with minimal configuration.
It's an end-to-end deployed AI-ML Project made using NumPy, Pandas, Sci-Kit Learn and Streamlit.
Practising mern.
Practising MERN.
Practise MERN.
Nike brand page created for practice purpose. It's created using react and Vite.
This repository is for my intership purpose at Oasis Infobyte. All the folders define the the tasks of Level 1.
I have done some sentiment analysis in python using two different techniques: VADER (Valence Aware Dictionary for Sentiment Reasoning) - Bag of words approach, Roberta Pretrained Model from š¤ and Hugging-face Pipeline.
This is a simple calculator made with HTML, CSS and JavaScript.
MERN-Based secured social media application with the facillity of end-to-end chat services.
This project is an email spam classifier that uses machine learning techniques to identify and filter spam emails. The classifier is trained on a labeled dataset of emails, distinguishing between spam and ham messages.
Personal portfolio website built using React Vite.
Config files for my GitHub profile.
Travel application built with React.