car-crashes

There are 0 repository under car-crashes topic.

• savagewheels

  kenamick / savagewheels

  :checkered_flag: 2D car crashing game armageddon

  gamesdlcarcar-crashesvideo-gamesdl-gamedestructioncpp
  Language:C++ 33

• marcosvppfernandes / chicagoteam_quanggang

  Prediction of severity of Car Crashes using Machine Learning

  crash-datacrashchicago-departmentmotor-vehicle-crashestraffic-crashmachine-learningmachine-learning-algorithmsflatiron-schoolflatironflatiron-school-projectinjurycar-crashesvehicleillinoistransportationxgboost-algorithm
  Language:Jupyter Notebook 3

• 281clo / Chicago_Car_Crash_Project

  Pinpointed the primary contributory causes of car accidents which were not related to human error.

  chicagocar-crashesclassification
  Language:Jupyter Notebook 2

• andythai / allegheny-crashes

  Data analysis of variables within car crashes in Pennsylvania's Allegheny county

  data-sciencecar-accidentsdata-analysiscar-crashesallegheny
  Language:Jupyter Notebook 2

• ray310 / NYC-Vehicle-Collisions

  Analysis of when and where New York City (NYC) vehicle collisions occur with a focus on collisions involving pedestrians and cyclists.

  clusteringdensity-based-clusteringnew-york-cityfoliumhotspot-analysisgeospatial-analysisgeospatial-visualizationcyclistspedestriansmotor-vehicle-collisionscar-crashes2d-heat-mapnypd-precinctsautomobilescollisionscrashesautomobile-collisionscyclist-injuriespedestrian-injuries
  Language:Jupyter Notebook 2

• Maskar / chicago_traffic_crashes

  This study creates machine learning models to predict the seriousness of car crashes using 2019 and 2020 crash reports from the publicly accessable database maintained by the Chicago Police Department. A car crash is considered serious if the crash results in an injury or the car is towed due to the crash. Models use categorical features that describe conditions at the time of the crash and crash causes to predict the required target. The current focus is to classify whether a crash results in an injury. All machine learning models are trained, validated, and tested on randomly split 2019 crash reports. The best model (along with all others) are then tested using the full set of 2020 crash reports.

  analysiscar-crashescategorical-featureschicagochicago-data-portalchicago-police-departmentcrash-reportsdata-scienceinjurymachine-learningmachinelearningstudytraffic-crashes
  Language:Jupyter Notebook 1