11 Kaggle Alternatives in Data Science Competitions

Daniel Morales
Jun 25, 2021


Data science competitions are a very particular field of applied machine learning, or what is commonly known as applied AI. From the point of view of a data scientist, it has the particularity of simulating a real environment for the solution of a machine learning problem. From the point of view of a company, it has the particularity of solving a problem in a collaborative way (following the wisdom of crowds) and obtaining the benefits derived from it: such as benchmarking, new ideas, different solutions.

As we mentioned in a previous blog post about data science competitions, some time ago several platforms were born among which is Kaggle and in which large technology companies in Silicon Valley and even Multinationals try to solve really complex problems with the help of outsiders, through something called "data science competitions". 

This was because internal talent could not solve these problems, because they did not have the time, resources or capabilities. Obviously these were really complex problems.

These data science competition platforms allow the company to access a global talent pool of data science specialists ranging from PHDs to self-taught individuals who set out on an adventure to solve the challenge posed by the company sponsoring a competition. 

The prizes are obviously exorbitant, with Netflix even paying $1 million for a machine learning solution. 

Sponsoring a competition there has an investment ranging from $20,000 USD to $100,000 USD on average. A luxury that only the big tech companies (or multinationals) can afford. 

What about startups? Well, unless you've raised a Series B or Series C, you might be able to afford to sponsor a $20,000 USD competition, or even have an internal team of data scientists to help you experiment or solve a problem with machine learning. 

But what about companies that are at an earlier stage and don't have these funds or that in-house talent? That is why we have dedicated this blog post to show other options for sponsoring data science competitions.

1- DataSource.ai



Company Targets: Startups & SMBs
Type Competitions: Cash Prizes
Competition System: Usually last 2-3 months each competition
Average Opened Competitions per Month: 1
Average Prize Money: Starting at USD $3.000

The focus of this platform is to democratize data science competitions. Other data science competition platforms are focused on very large companies, very high prizes and very complex problems. 

This translates into competitions that can only be paid for by companies with deep pockets, competitions that take months to complete, and that are made for data scientists and "super-senior" teams. 

At the end of the day sponsoring a $20,000 USD (or 1 million USD) competition is not for every type of company. 

So they decided to rethink the way data science competitions are built and decided to focus on startups of any size and from any part of the world, that can afford competitions that are in line with a startup budget, that don't take so long to be solved (8 weeks), that can launch more than one, two or three competitions (because they can afford it) and in which all kinds of data science talent can participate, from any level and from any part of the world. 


2- Numerai



Company Targets: Finance, Crypto
Type Competitions: Crypto Prizes
Competition System: Continuous
Average Opened Competitions per Month: Continuous

In the Numerai Tournament you build machine learning models on abstract financial data to predict the stock market. Your models can be wagered with the NMR cryptocurrency to earn performance-based rewards. Numerai's wagered models combine to form the Meta Model which controls Numerai's hedge fund capital in the global stock market. 

Here companies are not allowed to sponsor competitions, Numerai is the sponsor itself and is the one who delivers the rewards


3- International Data Analysis Olympiad (IDAHO)



Company Targets: Made by Yandex only
Type Competitions: Money Prize and Internships
Competition System: Usually last 1 year each competition
Average Opened Competitions per Year: 1
Average Prize Money: $10.000

IDAHO is an annual competition organized by the Higher School of Economics and Yandex. This event is open to all teams and individuals, be they undergraduate, postgraduate or Ph.D. students, company employees, researchers or new data scientists.



4- DrivenData



Company Targets: Social Companies
Type Competitions: Money Prize and Kudos
Competition System: Usually last 2-4 months each competition
Average Opened Competitions per Month: 2
Average Prize Money: $17.000


DrivenData brings cutting-edge practices in data science and crowdsourcing to some of the world’s biggest social challenges and the organizations taking them on


5- CodaLab




Company Targets: Social and Big Companies
Type Competitions: Knowledge
Competition System: Usually last 3-6 months each competition
Average Opened Competitions per Month: 1
Average Prize Money: Almost all are for knowledge 

Codalab open-source platform for computational research. The competitions are held for the sake of collaborative research and code testing.


6- DataHack & DSAT



Company Targets: Social and Big Companies
Type Competitions: Kudos
Competition System: Usually last 2-4 months each competition
Average Opened Competitions per Month: 1
Average Prize Money: All are hackathons without a final prize 

This platform basically allows you to compete with the best in the world on real-life data science problems, learn by working on real-world problems, showcase your expertise and get hired in top firms, build your profile, and be on the top of competitions and win lucrative prizes



7- Machine Hack



Company Targets: Social and Big Companies
Type Competitions: Money Prize and Kudos, Interviews
Competition System: Usually last 2-4 months each competition
Average Opened Competitions per Month: 1
Average Prize Money: All are hackathons without a final prize 


Machine Hack is an online platform for Machine Learning competitions. At Machine Hack, you get to test and practice your ML skills. In this platform, you have the opportunity to compete against hundreds of Data Scientists, with our industry curated Hackathons. 


8- Tianchi




Company Targets: Big Companies
Type Competitions: Money Prize and Kudos
Competition System: Usually last 3-6 months each competition
Average Opened Competitions per Month: 1
Average Prize Money: $100.000


Tianchi is a crowdsourcing community of global data scientists that hosts big data competitions in various industries. This Big Data Competition has million-dollar prize pools and real business test cases. You have the chance to compete against AI elites from around the world.


9- KDD Cup





Company Targets: Organized by ACM Special Interest Group
Type Competitions: Money Prize
Competition System: Usually last 1 year each competition
Average Opened Competitions per Month: 1
Average Prize Money: $12.000


Is the annual Data Mining and Knowledge Discovery competition organized by ACM Special Interest Group on Knowledge Discovery and Data Mining, the leading professional organization of data miners. Year to year archives including datasets, instructions, and winners are available for most years


10- vizdoom




Company Targets: Organized by VIZDOOM
Type Competitions: Money Prize
Competition System: Usually last 1 year each competition
Average Opened Competitions per Month: 1
Average Prize Money: No apply


VIZDOOM allows developing AI bots that play DOOM using the visual information (the screen buffer).


11- Crowd AnalytiX



Company Targets: Medium Size Companies
Type Competitions: Money Prize and Kudos
Competition System: Usually last 2-4 months each competition
Average Opened Competitions per Month: 1
Average Prize Money: $7.000

Data experts collaborate & compete to build & optimize AI, ML, NLP and Deep Learning algorithms

Conclusion

If you are a data scientist, you will definitely have a lot of learning and participation options. But make sure you also have a real chance to win!

If you are a company and you are thinking about solving a data science problem, don't hesitate to make the decision for the best!

“11 Kaggle Alternatives in Data Science Competitions”
– Daniel Morales twitter social icon Tweet

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