This is one of Kaggle challenges for predicts the Shelter Animal Outcomes
- Kaggle project page: https://www.kaggle.com/c/shelter-animal-outcomes
- Git repository: https://github.com/laercio-barbosa/animal-out.git
- Clone repository:
$ git clone https://github.com/laercio-barbosa/animal-out.gitEvery year, approximately 7.6 million companion animals end up in US shelters. Many animals are given up as unwanted by their owners, while others are picked up after getting lost or taken out of cruelty situations. Many of these animals find forever families to take them home, but just as many are not so lucky. 2.7 million dogs and cats are euthanized in the US every year.
Using a dataset of intake information including breed, color, sex, and age from the Austin Animal Center, we're asking Kagglers to predict the outcome for each animal. We also believe this dataset can help us understand trends in animal outcomes. These insights could help shelters focus their energy on specific animals who need a little extra help finding a new home. We encourage you to publish your insights on Scripts so they are publicly accessible.
Kaggle is hosting this competition for the machine learning community to use for data science practice and social good. The dataset is brought to you by Austin Animal Center. Shelter animal statistics were taken from the ASPCA. Glamour shots of Kaggle's shelter pets are pictured above. From left to right: Shelby, Bailey, Hazel, Daisy, and Yeti.
- Started: 9:28 pm, Monday 21 March 2016 UTC
- Ends: 11:59 pm, Sunday 31 July 2016 UTC (132 total days)
- Points: this competition does not award ranking points
- Tiers: this competition does not count towards tiers