Having knowledge is not enough to survive, for survival, and for assured victory, one needs to test his/her capabilities. To test wisdom and capabilities, competitions are extremely beneficial. In the case of data science, data scientists mostly work theoretically and get rare chance to experiment with real-world data themselves. With data science competitions and platforms, aspiring professionals are offered with a medium to interact and compete in solving real-life problems.
According to Towards Data Science, data competitions serve many purposes. One of the radical benefits is that they are the perfect place to learn best practices, accrue feedback on your work, and augment your skills. They can also serve as a channel for problem-solving and brainstorming by probing the multitude of crowdsourced solutions to big problems.
Therefore, here we have brought you the list of top data science competitions to test your knowledge and capabilities.
Kaggle is a great, if not the best platform for Data Science. It offers everyone to have a chance to get into the biggest data science community in the world. Kaggle enables data scientists and other developers and to host datasets, to engage in running machine learning contests, and to write and share code. It’s a crowd-sourced platform to attract, nurture, train, and challenge data scientists from all around the world to solve data science, machine learning, and predictive analytics problems.
The types of data science problems posted on Kaggle can be anything from attempting to predict cancer occurrence by examining patient records to analyzing sentiment to evoke by movie reviews and how this affects audience reaction. Competitions hosted on Kaggle have had far-reaching impacts such as enhancing and enabling state of the art HIV/AIDS research and improving traffic forecasting. Fundamentally, Kaggle has bestowed companies the opportunity to seek solutions from the best data scientist in the world and to have external pairs of eyes to look at the problems they are trying to solve.
CrowdANALYTIX also features data modeling competitions, diving into machine learning, artificial intelligence, deep learning, and natural language processing. These challenges are more informal, though no less rewarding. Like many of the other competitions listed here, some competitions are for the sake of learning, and others have a prize pool.
The platform consists of two “layers,” the machine layer of bots and the human layer of data scientists building those bots and algorithms. Here, the data competitions take a slight turn and are viewed as more of a work in progress for consistent iteration. Winning algorithms are moved to CrowdANALYTIX’s database and then monitored for fine-tuning. If the algorithm starts to degrade, it is moved back to the community to be adjusted or rebuilt.
Coda Lab is an open-source platform for computational research. The competitions are held for the sake of collaborative research and code testing. While they don’t offer prestigious prizes, they work together to create more efficient and reproducible code. Coda Lab features heavily on the programming and code-building of data and can be a good way to dip your feet into collaborative projects and challenges.
Topcoder is similar to Coda Lab in that it is also a collaborative effort to compile code testing and research. They have a wide array of challenges and competitions on their main site, ranging from data science to coding to web design. Many of these offer decent prize rewards, though some are simply for the sake of a challenge.
The main draw is the annual Topcoder Open, the “Ultimate Programming and Design Tournament.” It features a range of competitions such as algorithms, development, UI design, and quality assurance. The initial competitions are online, with the winners earning points that net them additional prizes and a trip to the TCO finals hosted in the US. The TCO also has smaller regional events to bring the competition to even more people. These events are only a day or two, but offer more international opportunities to get involved.
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.
The aim is to bridge the gap between the all-increasing complexity of Machine Learning models and performance bottlenecks of the industry. The participants will strive not only to maximize the quality of their predictions but also to devise resource-efficient algorithms.
This will be a team machine learning competition, divided into two stages. The first stage will be online, open to all participants. The second stage will be the offline on-site finals, in which the top 30 performing teams from the online round will compete at the Yandex office in Moscow.
DrivenData: Data Science Competitions for Social Good is an online challenge that usually lasts 2–3 months. where a global community of data scientists competes to come up with the best statistical model for difficult predictive problems that make a difference.
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. They run machine learning competitions to help non-profits, NGOs, governments, and other social impact organizations use data science in the service of humanity.
Part of DrivenData’s mission is to enable data scientists and non-profits to learn from the work that is done in these competitions. To this end, the code submitted by winners is released under an open-source license for others to learn from, use, and adapt.