Skip to content

#Rank 3 Solution of Machine Hack: Glass Quality Prediction Weekend Hackathon #6

Notifications You must be signed in to change notification settings

G-Slient/MachineHack-Glass-Quality-Prediction

Repository files navigation

Machine-Hack-Glass-Quality-Prediction-Weekend-Hackathon-6

#Rank 3 Solution of Machine Hack: Glass Quality Prediction Weekend Hackathon #6

We humans have been using glass since ancient times for a variety of applications from building construction to making decorative objects. With technology, glass and its applications have evolved, and today, we have different varieties of glass used for very different purposes from a computer monitor to a bulletproof car window depending on the grade of the glass produced. And not all grades or varieties are manufactured the same way. In this data science challenge, you as a data scientist must use the given data to predict the grade of the glass produced based on the given factors.

Given are 15 distinguishing factors that can provide insight into what grade of the glass is being produced. Your objective as a data scientist is to build a machine learning model that can predict the grade of glass based on the given factors.

Data Description:- The unzipped folder will have the following files.

  • Train.csv – 1358 observations.
  • Test.csv – 583 observations.
  • Sample Submission – Sample format for the submission.
  • Target Variable: class

Public Rank : 3rd
Private Rank: 3rd

About

#Rank 3 Solution of Machine Hack: Glass Quality Prediction Weekend Hackathon #6

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published