CS代写 COSI 126A: Final Project Kaggle

COSI 126A: Final Project Kaggle
Due by Dec. 3th
1 Overview – PUBG Finish Prediction on Kaggle
So, where we droppin’ boys and girls?

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Battle Royale-style video games have taken the world by storm. 100 players are dropped onto an island empty-handed and must explore, scavenge, and eliminate other players until only one is left standing, all while the play zone continues to shrink.
PlayerUnknown’s BattleGrounds (PUBG) has enjoyed massive popularity. With over 50 million copies sold, it’s the fifth best selling game of all time, and has millions of active monthly players.
The team at PUBG has made official game data available for the public to explore and scavenge outside of “The Blue Circle.” This competition is not an official or affiliated PUBG site – Kaggle collected data made possible through the PUBG Developer API.
You are given over 65,000 games’ worth of anonymized player data, split into training and testing sets, and asked to predict final placement from final in-game stats and initial player ratings.
What’s the best strategy to win in PUBG? Should you sit in one spot and hide your way into victory, or do you need to be the top shot? Let’s let the data do the talking!
Your task will be using the given data on Kaggle to predict users’ finish placement.
Please submit your team name and team members at the link given in LATTE before Oct. 29. The number of team members is up to 5. Larger groups are expected to have a higher score on Kaggle. Register on Kaggle.com and build a team. Your team name should be the same as your team name on Kaggle.

3 Final Deliverables 3.1 Kaggle Submission
You need submit your result on Kaggle before Dec. 3. We will collect your result on Kaggle based on your team name right after due time. Submissions after that will not be counted.
3.2 Write-Up
Your project write-up is due Dec. 3. It should be in PDF format and submitted on LATTE.
It should be 5-10 pages long and include the following elements:
• Team Name, Member names • Idea summary
• Implementation details
• Results and analysis
• What worked? What didn’t work? What surprised you along the way?
• Individual Contribution(what does each team member do, how do you split your works)
Please submit code demonstrating how to execute your work on LATTE.
Your grade will be decided by your score(performance) on Kaggle, the quality of your report and your presentation.

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