MachineHack has come up with an exciting way to spend your weekends. With a new addition to its hackathon series, MachineHack launches its first weekend hackathon the Metal Furnace Challenge.
Problem Statement & Description
Manufacturing of any alloy is not a simple process. Many complicated factors are involved in the making of a perfect alloy, from the temperature at which various metals are melted to the presence of impurities to the cooling temperature set to cool down the alloy. Very minor changes in any of these factors can affect the quality or grade of the alloy produced.
Given 28 distinguishing factors in the manufacturing of an alloy, your objective as a data scientist is to build a Machine Learning model that can predict the grade of the product using these factors.
You are provided with 28 anonymized factors (f0 to f27) that influence the making of a perfect alloy that is to be used for various applications based on the grade/quality of the obtained product.
Data Description
The unzipped folder will have the following files.
- Train.csv – 620 observations.
- Test.csv – 266 observations.
- Sample Submission – Sample format for the submission.
Target Variable: grade
Train.csv
Test.csv
Sample_Submission.xlsx
Bounties
The top 3 competitors will receive a cool AIM goodie bag.
Rules
- One account per participant. Submissions from multiple accounts will lead to disqualification
- The submission limit for the hackathon is 10 per day after which the submission will not be evaluated.
- All registered participants are eligible to participate in the hackathon
- This competition does not count towards our overall ranking points
- You will not be able to submit once you click the “Complete Hackathon” button. You may ignore this feature
- We ask that you respect the spirit of the competition and do not cheat
- This hackathon will expire on 20th April Monday at 7am IST
Evaluation
The leaderboard is evaluated using Multi Class Log loss (Cross-entropy loss) for the participant’s submission.
