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Hi there 👋

Hi there, I’m Shubham 👋

I’m a Full-Stack Web Developer i have hands on experience on Web technology React.js Django Docker Postgres Heroku Node.js MongoDB!

  • 🔭 I’m currently working on a Django-Docker-Nginx-PostgreSql
  • 🌱 I’m currently learning everything 🤣
  • 👯 I’m looking to collaborate with other
  • 🥅 2020 Goals: Study and contribute to Opensource projects
  • ⚡ Fun fact: I love to travel

Project Django in Heroku:

[Project 1]:
[Project 2]:

shubham zade's Projects

dockerdjangoreactproject icon dockerdjangoreactproject

Docker Guide - Build a fully production ready machine learning app with React, Django, and PostgreSQL on Docker

elyra icon elyra

Elyra extends JupyterLab Notebooks with an AI centric approach.

fake-review-detection-system icon fake-review-detection-system

Our project mainly focused on reviews, users, and business datasets from Yelp open data source. For reviews, we kept the unique id of each review, user id for people wrote the review, business id for restaurants that the user wrote it for, the review content, the rating according to the review, and the date when the review was writing. We also added in one geolocation character into the review data, which indicates the restaurant’s location where the review implied. We kept user id, the number of reviews that a user has written, the time since an user joined Yelp, and the average ratings reviews that an user has written from the user.json file. Last by not the least, we only included business id, name, business categories, geolocation information (city, state, postal codes, latitude, longitude), price range, ratings, number of reviews, and whether the restaurant is open or not from the business dataset. The Model is trained will be trained providing the labelled fake and true reviews. Support Vector Machine Classifier Pre-process: We used feature extraction module called Tfidf Vectorizer which is a scheme that transformed each review to a large sparse matrix with each cell represents a word and the frequency it appears in that review.

fwitter icon fwitter

Fwitter is an example 'real-world' application built on the scalable distributed database FaunaDB. The codebase is meant to be used in multiple articles that zoom in to a specific feature. You will find a plethora of well-commented examples ranging from an easy CRUD to advanced modeling, searching, join and sorting strategies.

grommet icon grommet

a react-based framework that provides accessibility, modularity, responsiveness, and theming in a tidy package

guides icon guides

Guides for learning + doing better web and app development. Created by Coding for Entrepreneurs.

html-css-class-completion icon html-css-class-completion

:chocolate_bar: Visual Studio Code extension that provides CSS class name completion for the HTML class attribute based on the CSS files in your workspace

interactive-reporting-in-jupyter-notebook icon interactive-reporting-in-jupyter-notebook

This sample shows how to create a Jupyter Notebook with the interactive pivot table and pivot charts components. This approach can be used for data analysis and data visualization purposes.

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