8 Data Science Competition Platforms Beyond Kaggle
Data competitions have become a popular way for data scientists and machine learning enthusiasts to showcase their skills and compete with others around the world. While Kaggle is the most well-known platform for data competitions, there are several other platforms that offer similar challenges and opportunities for participants.
1. Driven Data:
DrivenData is one such platform that focuses on social challenges. The company is a social enterprise that aims to bring data science solutions to organizations tackling the world's biggest challenges. DrivenData's competitions include building models against hate speech and misinformation, as well as other social impact challenges.
Numerai is an AI-powered, crowd sourced hedge fund that hosts a weekly tournament in which participants can submit their predictions on hedge fund obfuscated data and earn prizes in the company's cryptocurrency, Numeraire.
CrowdANALYTIX is another platform that hosts challenging data competitions. While it is less active now, it used to host a variety of competitions focused on deep learning and other data science topics.
Signate is a Japanese data science competition platform that offers a ranking system similar to Kaggle's. It hosts a variety of competitions that cover a range of topics, from natural language processing to image recognition.
Zindi is a data science competition platform from Africa that focuses on solving Africa's most pressing social, economic, and environmental problems. Its competitions cover a variety of topics, including agriculture, healthcare, and financial inclusion.
Alibaba Cloud is a Chinese cloud computing and AI provider that has launched the Tianchi Academic competitions, partnering with academic conferences such as SIGKDD, IJCAI-PRICAI, and CVPR. These competitions feature challenges such as image-based 3D shape retrieval, 3D object reconstruction, and instance segmentation.
7. Analytics Vidhya
Analytics Vidhya is the largest Indian community for data science, offering a platform for data science hackathons. Its competitions cover a variety of topics, including machine learning, deep learning, and data visualization.
CodaLab is a French-based data science competition platform that was created as a joint venture between Microsoft and Stanford University in 2013. It features a free cloud-based notebook called Worksheets for knowledge sharing and reproducible modeling.
Other minor platforms include CrowdAI from École Polytechnique Fédérale de Lausanne in Switzerland, InnoCentive, Grand-Challenge for biomedical imaging, DataFountain, and OpenML. A list of ongoing major competitions can be found at the Russian community Open Data Science.
In conclusion, while Kaggle may be the most well-known platform for data competitions, there are several other platforms that offer similar opportunities for data scientists and machine learning enthusiasts to showcase their skills and compete with others around the world. These platforms cover a wide range of topics and offer challenges that focus on solving some of the world's most pressing social, economic, and environmental problems.