Skip to content

A full-stack end-to-end web application developed on Django Framework which allows the users to get the forecast of the steel consumption of various categories of steel products for a particular region in India of desired year. The forecasted results are represented on a graph. and stored in database in real-time.

Notifications You must be signed in to change notification settings

amisha64/Steel-Edu

 
 

Repository files navigation

PROBLEM STATEMENT : To create a Machine Learning model to predict steel consumption in specific geographical regions. Optimized-Steel-Edu-Gif

TOOLS USED:

  1. Django Framework
  2. SQLite Database
  3. Python
  4. Machine Learning

TEAM DETAILS:

  1. Kashish – Vellore Institute of Technology, Chennai
  2. Naman Singh Raj – Bhilai Institute of Technology, Durg
  3. Nidhi Priya – Birla Institute of Technology,Mesra, Patna
  4. Amisha Kirti – C. V. Raman Global University, Bhubaneswar
  5. Pragya Kumari – Birla Institute of Technology, Mesra, Ranchi

About

A full-stack end-to-end web application developed on Django Framework which allows the users to get the forecast of the steel consumption of various categories of steel products for a particular region in India of desired year. The forecasted results are represented on a graph. and stored in database in real-time.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • JavaScript 39.2%
  • CSS 38.7%
  • HTML 14.9%
  • Python 7.2%