0xpranjal.eth's Projects
This repository contains my practise files and application s made using Bokeh visualisation tools.
Solutions to the coursera course, Introduction to Household Water Treatment and Safe Storage
A machine learning model, deployed using flask. Made into a web app that can help you classify species of Iris flower and go through the dataset.
The Julia Programming Language
Finding the optimum number of clusters for k-means classification
Production-Grade Container Scheduling and Management
This repository contains the sample code of Neural Networks implementation in multiple programming languages
NFT API that returns resolved metadata and has all information about all NFT collections, users, transactions. Cross-Chain NFT API.
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Making a binary classifier to detect pneumonia using chest x-rays images.
All Algorithms implemented in Python
Testing different ansatzes for QSVM on the breast cancer dataset
Sources of the Microsoft Quantum Development Kit documentation
This repo is a one stop destination to find resources for learning various domains. You can find the roadmap for any domain here.
This repo contains code and slides for Road to Decipher Bootcamp
A collection of notebooks and different prediction models that can predict the stock prices. Also a comparison of how all these models performed.
Chatbot helping people make well-informed and calculated investments.
A python package for better analysis of the Stock Market.
The sinking of the Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the widely considered “unsinkable” RMS Titanic sank after colliding with an iceberg. Unfortunately, there weren’t enough lifeboats for everyone onboard, resulting in the death of 1502 out of 2224 passengers and crew. While there was some element of luck involved in surviving, it seems some groups of people were more likely to survive than others. In this challenge, I was asked to build a predictive model that answers the question: “what sorts of people were more likely to survive?” using passenger data (ie name, age, gender, socio-economic class, etc).
This repository contains my tasks for TSF Machine Learning internship
weavy is a prototype decentralized mail system, running on the Arweave network
Repository contains python code for web-scraping using BeautifulSoup
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent