Exam Mark Prediction AI Challenge
The aim of this challenge is to predict the exam score given the student's performance.
Welcome to Exam Mark Prediction AI Challenge!
The aim of this challenge is to predict the exam score given the student's performance. The dataset consists of 3 CSV files:
The dataset consists of the following attributes:
- Parental Level of Education
- Test Preparation Course
- Reading Score
- Writing Score
- Math Score (Target Variable)
As part of the "train.csv" file provided for training. No additional data may be used for training.
The test set consists of "test.csv" for all the same attributes as "train.csv" except for the target column. There is an additional "sample_submission.csv" provided to give an example submission.
Please refer to the Submission Guidelines for the final format of the submission.
The score is displayed in reverse order of Root Mean Square Error (RMSE). "train.csv" file contains the data required for training.
The output of the model should be "output.csv" containing the following columns in this exact order for predictions on test.csv:
- idx (Row index of TEST.csv data)
- math_score (Target Attribute)
A "Sample-Submission.csv" is also given for reference which already contains the correct format required for submission.
How to make a submission?
- Click on "My Submission"
- On the next page, click on "+ New Submission"
- Upload your CSV in the next page and click on "Submit for Review"
- You must submit your CSV file by uploading the CSV in the "My Submissions" section of this challenge.
- Your submission will be auto graded and you will be able to see your results instantly.
- If there is any error in the submission, your final score will be marked as 0.
- Root Mean Squared Error (RMSE) will be used for evaluation
- If the scores are tied, the person reaching the score FIRST will get the better rank.
- We are using an automatic anti-cheat system. Our system flags submission which has low trust scores. Manually modifying your submission CSV (via comparison of any form etc.), using image comparison techniques (pixel matching, file size matching, etc.), in any form, can lead to your disqualification without any notice.
- The participants must use only the provided dataset for training.
- The submission should be in a proper format as described by "Submission Guidelines".
- Late submission will not be accepted beyond the provided deadline (Indian Standard Time).
NOTE: We may request the code files if there is any discrepancy in your score. Your score will be marked invalid, or you can be disqualified if the request for code is not fulfilled by you.
- The winner will receive a cash prize of 5000 INR.
- The participants with a successful submission will get a certificate of participation.
- Top 3 participants will receive a permanent place in Dockship's "Hall of Fame".
- Top 3 participants will receive goodies from Dockship.
Top 10 Participants will also earn Dockship gems:
- Rank 1: 500 💎
- Rank 2: 250 💎
- Rank 3: 100 💎
- Rank 4: 50 💎
- Rank 5: 50 💎
- Rank 6: 50 💎
- Rank 7: 50 💎
- Rank 8: 50 💎
- Rank 9: 50 💎
- Rank 10: 50 💎