The Kaggle platform

To start using Kaggle, you will have to create an account. You can register with your email and password or authenticate using your Google account directly. Once registered, you can start by creating a profile with your name, picture, role, and current organization. You then can add your location, which is optional, and a short personal presentation as well. After you perform an SMS verification and add some minimal content on the platform (run one notebook or script, make one competition submission, make one comment, or give one upvote), you will also be promoted from Novice to Contributor. The following figure shows a checklist for how to become a contributor. As you can see, all items are checked, which means that the user has already been promoted to the Contributor tier.

Figure 1.1: Checklist to become a contributor

With the entire Contributor checklist completed, you are ready to start your Kaggle journey.

The current platform contains multiple features. The most important are:

• Competitions: This is where Kagglers can take part in competitions and submit their solutions to be scored.
• Datasets: In this section, users can upload datasets.
• Code: This is one of the most complex features of Kaggle. Also known as Kernels or Notebooks, it allows users to add code (independently or connected to datasets and competitions), modify it, run it to perform analysis, prepare models, and generate submission files for competitions.
• Discussions: In this section, contributors on the platform can add topics and comments to competitions, Notebooks, or datasets. Topics can also be added independently and linked to themes such as Getting Started.

Each of these sections allows you to gain medals, according to Kaggle’s progression system. Once you start to contribute to one of these sections, you can also be ranked in the overall Kaggle ranking system for the respective section. There are two main methods to gain medals: by winning top positions in competitions and by getting upvotes for your work in the Datasets, Code, and Discussions sections.

Besides Competitions, Datasets, Code, and Discussions, there are two more sections with content on Kaggle:

• Learn: This is one of the coolest features of Kaggle. It contains a series of lectures and tutorials on various topics, from a basic introduction to programming languages to advanced topics like computer vision, model interpretability, and AI ethics. You can use all the other Kaggle resources as support materials for the lectures (Datasets, Competitions, Code, and Discussions).
• Models: This is the newest feature introduced on Kaggle. It allows you to load a model into your code, in the same way that you currently add datasets.

Now that we’ve had a quick overview of the various features of the Kaggle platform, the following sections will give you an in-depth view of Competitions, Datasets, Code, Discussions, Learn, and Models. Let’s get started!