{"id":2145,"date":"2020-09-29T14:56:43","date_gmt":"2020-09-29T14:56:43","guid":{"rendered":"https:\/\/data-science.gotoauthority.com\/2020\/09\/29\/international-alternatives-to-kaggle-for-data-science-machine-learning-competitions\/"},"modified":"2020-09-29T14:56:43","modified_gmt":"2020-09-29T14:56:43","slug":"international-alternatives-to-kaggle-for-data-science-machine-learning-competitions","status":"publish","type":"post","link":"https:\/\/wealthrevelation.com\/data-science\/2020\/09\/29\/international-alternatives-to-kaggle-for-data-science-machine-learning-competitions\/","title":{"rendered":"International alternatives to Kaggle for Data Science \/ Machine Learning competitions"},"content":{"rendered":"
\n

By Frederik Bussler<\/a>, Growth at Apteo<\/b>.<\/p>\n

<\/p>\n

By author.<\/em><\/p>\n

We\u2019ve all heard of Kaggle, but that also means there\u2019s more competition \u2014 recently, Kaggle reached 5 million users. Further, not all competitions are open to everyone in the world. Here\u2019s the policy of one competition, for instance:<\/p>\n

\n

\u201cMembers of the Kaggle community who are not United States Citizens or legal permanent residents at the time of entry are allowed to participate in the Competition but\u00a0are not eligible to win prizes<\/strong>. If a team has one or more members who are not prize eligible, then the entire team is not prize eligible.\u201d<\/em><\/p>\n<\/blockquote>\n

By trying out other competition platforms, you can be a \u201cbig fish in a small pond,\u201d as there are a lot fewer competitors.<\/p>\n

Keep in mind that AI competitions aren\u2019t the end-all-be-all if you want to enter the industry, as you\u2019ll need knowledge in statistics, computing, communication, and more \u2014 not just knowing how to build models.<\/p>\n

Besides ranking in competitions, you\u2019ll want to work on practical projects that you can share with the world. Ideally, your projects can resonate with non-technical audiences as well, such as hiring managers who often don\u2019t understand the intricacies of the field. To do so, you can use no-code analytics tools like\u00a0Apteo<\/a>\u00a0that let you share very simple and easy-to-understand analyses.<\/p>\n

That being said, let\u2019s dive in.<\/p>\n

\u00a0<\/p>\n

1.\u00a0DrivenData<\/a>
\n<\/h3>\n

\u00a0<\/p>\n

DrivenData is open to everyone around the world (with the exception of OFAC sanctioned countries like Cuba, Iran, Iraq, North Korea, Sudan, and Syria).<\/p>\n

<\/p>\n

DrivenData Eligibility rules. Captured by author.<\/em><\/p>\n

Current competitions include Alzheimer\u2019s research, hateful meme detection, predicting flu vaccines, and more.<\/p>\n

\u00a0<\/p>\n

2.\u00a0CROWDANALYTIX<\/a>
\n<\/h3>\n

\u00a0<\/p>\n

CROWDANALYTIX features competitions like cement quality forecasting, with participants from around the world. Currently, competitions are slowing down, but there\u2019s also a great\u00a0blog<\/a>\u00a0to learn more about data science topics in the meantime.<\/p>\n

Check out\u00a0Damian Boh<\/a>\u2019s experience working on a CrowdANALYTIX competition:\u00a0How I Won Top Five in a Deep Learning Competition<\/a><\/p>\n

\u00a0<\/p>\n

3.\u00a0Signate<\/a>
\n<\/h3>\n

\u00a0<\/p>\n

<\/p>\n

Photo by\u00a0Louie Martinez<\/a>\u00a0on\u00a0Unsplash<\/a>.<\/em><\/p>\n

Signate is basically Japan\u2019s Kaggle and has current competitions about vehicle driving image recognition, flattening the curve, and more.<\/p>\n

\u00a0<\/p>\n

4.\u00a0Zindi<\/a>
\n<\/h3>\n

\u00a0<\/p>\n

Zindi is a pan-African data science competition platform with challenges including African language NLP, insurance recommendations, a mental health chatbot, and more.<\/p>\n

GIZ AI4D Africa Language Challenge – Round 2<\/a><\/p>\n

\u00a0<\/p>\n

5.\u00a0Alibaba Cloud Tianchi<\/a>
\n<\/h3>\n

\u00a0<\/p>\n

Alibaba\u2019s Tianchi platform boasts 400,000 data scientists on its platform, working on challenges like image-based 3D shape retrieval, 3D object reconstruction, and instance segmentation.<\/p>\n

\u00a0<\/p>\n

6.\u00a0Analytics Vidhya<\/a>
\n<\/h3>\n

\u00a0<\/p>\n

Analytics Vidhya, besides being a great data science resource, is India\u2019s go-to data science competition platform, with current challenges including loan prediction, sales prediction, times series forecasting, recommendation engines, and more.<\/p>\n

\u00a0<\/p>\n

7.\u00a0CodaLab<\/a>
\n<\/h3>\n

\u00a0<\/p>\n

CodaLab is a French-based data science competition platform popular in Europe, created as a joint venture between Microsoft and Stanford University in 2013.<\/p>\n

Today, CodaLab boasts 40,000 users and 1,000 competitions, including an on-going\u00a0robotics vision challenge<\/a>.<\/p>\n

\u00a0<\/p>\n

Conclusion<\/h3>\n

\u00a0<\/p>\n

You can\u2019t win Kaggle prizes as a non-American, but there are fortunately many regional alternatives available.<\/p>\n

While we didn\u2019t cover regions like South or Central America \u2014 which don\u2019t have their own local platforms \u2014 you can use truly open-access sites like DrivenData no matter where you are.<\/p>\n

Original<\/a>. Reposted with permission.<\/p>\n

\u00a0<\/p>\n

Related:<\/b><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

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