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Hi šŸ‘‹, I'm Sivanesh B

A passionate web developer from India

About me:

  • šŸŒ± Iā€™m currently learning web development and api

  • šŸ’¬ Ask me about who are you really?? || python && javascript

  • šŸ“« How to reach me [email protected]

  • āš” Fun fact i was a ex professional Fortnite and Valorant player.

šŸŒ Socials:

Facebook Instagram LinkedIn Stack Overflow Twitch Twitter

šŸ’» Tech Stack:

C C++ Java Python HTML5 CSS3 JavaScript Markdown PHP PowerShell Shell Script Google Cloud Windows Terminal AWS Heroku Netlify Azure Firebase GithubPages Anaconda Vercel Angular Bootstrap Django Express.js Flask Socket.io MongoDB MySQL Next JS NodeJS Nodemon React React Native React Query React Router React Hook Form Redux SQLite Keras NumPy Pandas C C++ Java Python HTML5 CSS3 JavaScript Markdown PHP PowerShell Shell Script Google Cloud Windows Terminal AWS Heroku Netlify Azure Firebase GithubPages Anaconda Vercel Angular Bootstrap Django Express.js Flask Socket.io MongoDB MySQL Next JS NodeJS Nodemon React React Native React Query React Router React Hook Form Redux SQLite Keras Yarn Apache Adobe After Effects Matplotlib NumPy PyTorch scikit-learn TensorFlow Pandas Docker ElasticSearch Kubernetes Postman Portfolio Raspberry Pi Terraform

šŸ“Š GitHub Stats:



āœļø Random Dev Quote

Sivanesh B's Projects

ecommerce-spices icon ecommerce-spices

This is a responsive Ecommerce website (frontend) for buying species made with Bootstrap CSS framework

lan-chat-server icon lan-chat-server

This Project can be used for chatting in Local Area Network. Also this is my Final Year Academic project

movie-recommendation-system icon movie-recommendation-system

Recommender systems are no joke. They have found enterprise application a long time ago by helping all the top players in the online market place. Amazon, Netflix, Google and many others have been using the technology to curate content and products for its customers. Amazon recommends products based on your purchase history, user ratings of the product etc. Netflix recommends movies and TV shows all made possible by highly efficient recommender systems.

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