Overview
Who this competition fits
Beginners who want a low-friction first competition on a learning platform with DataLab notebooks.
Read the original official blurb
Traffic congestion is an issue faced by urban centers. The complexity of managing traffic increases yearly for several reasons, generating higher fuel consumption and increased emissions. The complexity is even higher in New York City (NY), with its exceptionally complex road network. Efficiently managing traffic flows in such a bustling environment is crucial. This challenge allows you to try to relieve traffic congestion in NY. You'll analyze historical traffic and weather data. The end goal is to identify factors contributing to congestion and develop a predictive model that forecasts traffic volumes based on these factors. In this competition, you will focus on the following key tasks: Scoring notes: This competition is for helping to understand how competitions work. This competition will not be judged.
Preparation
From registration to a first submission
- 01
Python or R basics
- 02
DataCamp / DataLab workflow
- 03
pandas or tidyverse
Before you commit: Even learning competitions can stall if you have never turned analysis into a clean submission notebook.
Source
How this page was assembled
Competition information is structured from the official page. Scores are platform estimates for decision support; official rules take precedence.
- Official competition page
- DataCamp
- Last checked
- Aug 12, 2024