Adarsh Sethi's repositories
journey-to-hackerank-SQL-gold-badge
This repository contains the solutions that I have submitted to earn SQL Gold Badge on the Hacker Rank Platform. To view, all my achievements follow the link to my Hacker-Rank profile.
italian-delicaciess
A responsive food ordering website with an API integrated Google OAuth 2.0 for user authentication. Used Inheritance-based template design to create recyclable views for login, adding items to cart, checkout, and displaying all orders on the dashboard. Feature to add new items right from the Django admin for rapid scalability.
Hacker-Rank-Days-of-Statistics
This repository contains the solutions that I have submitted to earn Gold Badge for Statistics on the Hacker Rank Platform. To view, all my achievements follow the link to my Hacker-Rank profile.
The-Cryptographer-App
A multi level encrypting decrypting application in the Cpp language can be used to strengthen the security of authentication modules working with passwords, security keys, authentication keys, tokens, and cookies.
character_recognition_app
- Dockerised Flask Application integrated with CNN model to predict a character from a given a Handwritten Devanagiri character contained in an image. Used an F1-Score (98.9%) to evaluate the model’s accuracy.
Chatire
:speech_balloon: Real time Chat application built with Vue, Django, RabbitMQ and uWSGI WebSockets.
data-structures-algorithms-level-up-bootcamp
C++ Code Repository.
facebook_comments_analysis
A Selenium-based Facebook comments collection and analyzer tool. Connected with a Django REST for powering the Class-based Views and a React.JS interface. MySQL is used as a data store.
the-bravehearts
A responsive blogging website with Node.js backend coupled with Mongo DB to share the heroic deeds of the Indian warrior. Implemented dynamic URL routing using Express to create unique pages for posts combined with recyclable components written in EJS templating language
Kaggle-competitions
1-Predicting Employee Attrition 2-Predicting Car Prices 3-Image Classification Model
markdown-cheatsheet
Markdown Cheatsheet for Github Readme.md
markdown-here
Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.
nodejs-quickstart
This repository contains code samples for the Node.js Quick Start blog post series
thought-galaxy
A react app built with custom reusable components for Header, Footer, and Notes Cards for keeping track of all ideas, tasks, to-do lists, notes, reminders, shopping lists, etc
udemy-docker-mastery
Udemy Course to build, compose, deploy, and manage containers from local development to high-availability in the cloud
Yahoo-Finance-API-client
Dashboard: 1. Users should be able to select multiple stocks 2. In each stock tab, users should be able to select the date range and fetch High, Low, Mean, Median stock prices 3. Model the obtained data and find out mean and variance. You can read about the variance here: https://www.investopedia.com/terms/v/variance.asp Also show these two values 4. Find the #times and time stamps where stock moved outside this range (mean + std. deviation, mean - std. deviation). Call me up to understand more. The result should give only the first instance it happened 5. Along with showing date-time stamps when it moved out of that range, also show the time-stamp when it returned in the range for the first time.