The Kaggle Blueprints

An article series analyzing Kaggle competitions’ winning solutions for lessons we are able to apply to our own data science projects

Should you ask any successful Kaggler what suggestions they need to improve your data science skill set, all of them have the identical answer. They’ll inform you to review the highest solutions of accomplished Kaggle competitions.

Kaggle is a platform for data science competitions for various forms of problems. Competitors compete by constructing Machine Learning models and submitting their predictions. The competitor with probably the most accurate predictions takes home a prize.

Despite the competitive surrounding, the Kaggle community nurtures a mindset of learning. The platform itself encourages public sharing of approaches during and after the competitions.

Because of this, a accomplished Kaggle competition is a pool of learning resources of state-of-the-art Machine Learning techniques.

We will differentiate between two forms of resources:

• (in type of discussions or Notebooks): resources showing quite a lot of different techniques to approach the issue
• (in type of high-level write-ups and code on GitHub): resources showing which techniques worked well for the issue

While the resources in themselves are frequently well structured, it could be difficult to navigate the variety of resources to extract the relevant information after the competition has ended.

Thus, this text series reviews and summarizes the most well-liked and successful techniques utilized in Kaggle competitions. Nevertheless it won’t review the precise solutions for the precise problem setting. As a substitute, we’ll analyze the Kaggle competition’s winning solutions and extract the “blueprints” for lessons we are able to apply to our data science projects.

… [W]e will analyze the Kaggle competition’s winning solutions and extract the “blueprints” for lessons we are able to apply to our data science projects.

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You could find the gathering of articles on this series here:

The Kaggle Blueprints: Unlocking Winning Approaches