Why is Kaggle so scary?

In this article, we will talk about Kaggle. You know, this huge platform where you can practice machine learning, deep learning, etc.

When dealing with data science, Kaggle is the go-to platform.

What is Kaggle? Kaggle is a data science platform acquired by Google in 2017. So it includes competitions where you can win money. And do you see the famous recommendation algorithm of Netflix? Well, it was a competition on this very platform, and the prize was $1 million, which is pretty motivating, right?

But first and foremost, Kaggle is educational, so you can find tutorials, datasets, and free competitions. Also, there is a big community to help you if you're stuck.

So, the problem will come with the score.

We've reached a plateau. Does that mean we suck? That Kaggle isn't for us?

What would be interesting to improve your model? So, yes, you need to make several attempts. It could be discouraging, but that is normal. Also, what is important is the algorithms.

Ensemble methods is the best algorithm for those types of competitions. For example, you can use Random Forest.

Why? Well, this is an all-purpose algorithm. That's quick to train because it can be parallelized. So definitely try this algorithm every time you try to do a competition on Kaggle.

Now, is Kaggle good for learning data science?

First of all, it's important to understand that doing data science on Kaggle is a special process.

In truth, it doesn't correspond to the real world. The datasets are a little too clean, even if you can find datasets with a lot of data cleaning to do. But you have to look for these datasets. On the other hand, even if one of the secrets is to use a set of methods, you have to work hard on feature engineering to get the score right. Which is good news. We're focusing on one of the most important parts of a data science project.

In conclusion, I really encourage you to use this platform to improve your skills. As I've said, you have also a community. You can get scores if you participate in those communities. So don't hesitate to do that.