Teaming and networking

However, the computational power plays its part, the human expertise and ability only can make the real difference in a Kaggle competition. Sometimes a competition to be handled successfully requires the collaborative efforts of a team of contestants. Apart from recruitment competitions, where the sponsor may require individual participants for a better evaluation of their abilities, usually there is no limit to forming teams during competitions. Usually the teams can be at maximum made of five contestants. Teaming has its own advantages because it can multiply the efforts on finding a better solution, since a team can spend more time all together on the problem and different skills can be of great help: not all data scientists have the same skills or the same level of skill in the different models and data manipulations.

Anyway, teaming is not all positive. Coordinating different individuals and different efforts toward a common goal may prove not so easy and some suboptimal situations may arise. The usual problem with teams is when part of the participants is not involved or simply idle, but the worst is surely when, a more rare occurrence, someone infringes the rules of the competition (to the detrimental of everyone since the all team could be disqualified) or even spies on the team in order to advantage other ones.

In spite of any negative side, teaming in Kaggle competition is a great opportunity to know better other data scientists, to collaborate for a purpose and to achieve more, since Kaggle rules do reward teams in respect of lonely competitors. Teaming together is not the only possibility of networking in Kaggle, though it is certainly the more profitable and interesting for the participants. You can actually network with others by discussions on the forums, by sharing datasets and notebooks during competitions. All these opportunities on the platform can help you to know other data scientist and to be recognized by them.

There are also quite many occasions to network with other Kagglers outside of the Kaggle platform itself. First of all, there are a few Slack channels that can be helpful. For instance, KaggleNoobs (see: https://www.kaggle.com/getting-started/20577) is a channel, opened up 5 years ago, that feature many discussions about Kaggle competitions and they have a supportive community that can help you if you have some specific problem with code and models. There are quite a few other channels around devoted to exchanging opinions about Kaggle competitions and data science related topics. Some channels are organized on a regional or national basis. For instance, the Japanese channel Kaggler-ja (http://kaggler-ja-wiki.herokuapp.com/) or the Russian community, created six years ago, Open Data Science Network (https://ods.ai/) which later opened also to non-Russian speaking participants. The Open Data Science Network (mostly simply known as ODS) doesn’t simply offer a Slack channel but also courses on how to win competitions, events, and reporting on active competitions around on all known data science platforms (see https://ods.ai/competitions).

Apart from Slack channels, also quite a lot of local meetups themed about Kaggle in general or about specific competitions have sprout out, some for short time, others for longer. A meetup on Kaggle competition, usually built around a presentation from a competitor who wants to share her or his experience and suggestions, is the best situation to meet other Kagglers in person, to exchange opinions and to build alliances for participating together in data science contests. In this league, a mention apart is for Kaggle Days (https://kaggledays.com/), built by Maria Parysz and Paweł Jankiewicz, a renowned Kaggle competitor. The Kaggle Days organization arranged a few events in major locations around the World (https://kaggledays.com/about-us/) with the aim of bringing together a conference of Kaggle experts (which had to come to an abrupt stop due to the COVID-19 pandemic) and it created a network of local meetups in different countries which are still quite active (https://kaggledays.com/meetups/).