Mini Challenge Data Science Problems

Please read all the problems carefully and prepare your solutions in a PDF/Docx only. Once you are ready with solutions, please upload the file by registering in the above window. "BEST OF LUCK"

IPL Score Prediction

The following Dataset (IPL_Scores.csv) contains match data from IPL matches. It contains the following columns

Match_id :- ID number of the match
Innings_No :- First innings or second innings ( a number other than 1 or 2 is not permissible)
RUNS_15 :- Runs as of the 15th over
Over_id_15 :- A number other than 15 here indicates that the innings was finished in less than 15 overs (either all out or match won)
Bowler_Wicket_15 :- Number of wickets as of the 15th over
Ball_id_15:- Number of balls bowled as of the 15th over
RUNS_20 :- The final score of the match (To be predicted)

The objective is to create a machine learning model to predict the final runs scored by a team (last column), given the data from the other columns. Send your submissions to mythreya.lingala@careerlauncher.com. They will be evaluated with a separate test set and scored accordingly.

Downlaod IPL Scores

Exam Score Prediction

The following Dataset (Exam_Data.csv) contains match data from IPL matches. It contains the following columns

USER_ID :- Id number of student
NMOCKS :- Number of mock tests written by the student
BEST_MOCK :- The best percentile scored by the student in a mock test
TOP3_MOCK :- The average percentile of the three best mock tests given by the student
TOP5_MOCK :- The average percentile of the five best mock tests given by the student
TOP8_MOCK :- The average percentile of the eight best mock tests given by the student
AVG_MOCK :- Average mock test percentile
DIFF_ATT :- percentage of difficult questions attempted across mock tests (between 0 and 1)
DIFF_ACC :- accuracy in difficult questions across mock tests (between 0 and 1)
EASY_ATT :- percentage of easy questions attempted across mock tests (between 0 and 1)
EASY_ACC :- accuracy in easy questions across mock tests (between 0 and 1)
EXAM_PERC :- Percentile scored in the public exam by the student

The objective is to create a machine learning model to predict the final percentile a student will score in the public exam (last column) given their performance in the mock tests (remaining columns). Send your submissions to mythreya.lingala@careerlauncher.com. They will be evaluated with a separate test set and scored accordingly.

Download Exam Data

Mini Challenge

Please read all the problems carefully and prepare your solutions in a PDF/Docx only. Once you are ready with solutions, please upload the file by registering in the above window. "BEST OF LUCK"

IPL Score Prediction

Exam Score Prediction

Problems 3

Problems 4

Problems 5

Problems 6

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