Hackathons are a great way for people to not only learn more about technology but also showcase their existing skills by making projects often in a few hours. This dataset contains data collected from 200 participants of a hackathon conducted for high school students. A lot of columns have been deleted but the remaining columns can be useful to understand the demographic and interests of someone participating in these kind of events.

Dataset

This dataset was created by Souphaxay Naovalath

Released under Apache 2.0

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Dataset

This dataset was created by Saumya Mishra 536

Released under Apache 2.0

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Dataset

This dataset was created by Sayf El Kaddouri

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Dataset

This dataset was created by Ajay Pandey

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Dataset

This dataset was created by ShikharShrivastava

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It contains the following files:

Dataset

This dataset was created by Makorn MGodK

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Dataset

This dataset was created by Amine Yaiche

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It contains the following files:

Dataset

This dataset was created by MV30

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Dataset

This dataset was created by TD1989

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It contains the following files:

Dataset

This dataset was created by Aishik Rakshit

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Dataset

This dataset was created by sanjeethjveigas

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FAQ

The solutions are evaluated on two criteria: predicted future Index values and allocated energy from a newly discovered star 1. Index predictions are evaluated using RMSE metric 2. Energy allocation is also evaluated using RMSE metric and has a set of known factors that need to be taken into account

Every galaxy has a certain limited potential for improvement in the index described by the following function:

Potential for increase in the Index = -np.log(Index+0.01)+3

Likely index increase dependent on potential for improvement and on extra energy availability is described by the following function:

Likely increase in the Index = extra energy * Potential for increase in the Index **2 / 1000

Constraints

in total there are 50000 zillion DSML available for allocation no galaxy should be allocated more than 100 zillion DSML or less than 0 zillion DSML galaxies with low existence expectancy index below 0.7 should be allocated at least 10% of the total energy available

Submit format

Dataset

This dataset was created by Akshit Bhalla

Released under CC0: Public Domain

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Dataset

This dataset was created by Omodolapo Adedeji

Released under Apache 2.0

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Context

AV HackLive - Guided Community Hackathon!

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Data Science competitions can be daunting for someone who has never participated in one. Some of them have hundreds of competitors with top notch industry knowledge and splendid past record in such hackathons.

Thus a lot of beginners are apprehensive about getting started with these hackathons

The top 3 questions that are commonly asked:

Is it even worth it if I have minimal chance of winning? How do I start? How can I improve my rank in the future? Let’s answer the first question before we go further.

Dataset

This dataset was created by Bunty Shah

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Dataset

This dataset was created by saravanakumar

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Given below are three files that you will be using for the challenge. Download all the files. The training file has a labelled data set. However, the test file shall only have the features. Work out your algorithm for the same and make predictions on the test file after which you have to create a submissions.csv file that will be evaluated. You may refer to the sample_submission.csv file in order to understand the overall structure of your submission. The dataset consists of overall stats of players in ODIs only.

File descriptions:

train.csv - the training set test.csv - the test set sampleSubmission.csv - a sample submission file in the correct format Data fields id - an anonymous id unique to the player Name - Name of the player. Age - Age 100s - Number of centuries of the player 50s - Number of half centuries of the player 6s - Total number of sixes hit by the player Balls - Number of balls bowled by the player Bat_Average - Average batting score Bowl_Strike_Rate - average number of balls bowled per wicket taken Balls faced - Number of balls faced Economy - average number of runs conceded for each over bowled. Innings - Number of innings played Overs/strong> - Number of overs bowled Maidens - Overs when no run was conceded Runs - Total runs scored by the player Wickets - Number of wickets taken Ratings - Final rating of the player

Dataset

This dataset was created by Gaurav Dutta

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