Is Kaggle enough for data science?

No. It will probably help you land an interview, but certainly not a job on its own. Firstly, data science jobs come in many flavours. Not all of them require optimising a predictive machine learning model like Kaggle.

Why Kaggle will not make you a great data scientist?

Kaggle Contests Can Never Simulate Real-World Problems In other words, data scientists in competition get to work right away on data that is already cleaned. Real-world problems, on the other hand, are a completely different animal altogether, which Kaggle competitions never represent.

Are Kaggle competitions useful?

This basically means that companies use Kaggle competitions as a way of finding out the different solutions to a problem. These solutions are created by people all over the world with different academic and industry backgrounds which only provides a deeper exposure to machine learning.

Can you become a data scientist with Kaggle?

Kaggle is a great place to learn and master data science skills, but it could easily become overwhelming if you don’t have strong knowledge of the basics. Python and R are the most popular programming languages for data science.

Are Kaggle competitions good for CV?

If you are an experienced data scientist, you will be better off using your limited resume space to describe your work experience. A Kaggle competition would not count as a true independent project, as Kaggle presents you with the question as well as with cleaned data.

Is Kaggle certificate useful?

I would approach this question as a data science problem.

Should I use my real name on Kaggle?

In the profile setting for a user’s display name, the Kaggle directions advise, “We recommend using your full name.” However, I’m wondering whether that is a good strategic decision, for reasons related to the potential for unconscious bias that might provide a disadvantage to those with a name that differs from the …

Do companies recruit from Kaggle?

Doing well on Kaggle can help data scientists land an interview, but certainly not a job on its own. This means that most companies may not base a hiring decision on a candidate’s Kaggle ranking alone.

Is Kaggle good for resume?

But you can definitely write to your resume when you learn much and do well in multiple Kaggle competitions, especially for entry level data science job. A good kaggle rank and experience can make a candidate outstanding from many competitors who can only list a few skill keywords and school projects on their resumes.

How do you become a pro kaggle?

You need to get 5 upvotes per dataset in at least 3 datasets. Self upvotes and votes by novices are excluded. This is a relatively hard task too, since you have to upload your own data. Note that you must indicate the maximum of details (data description, source …etc) to increase the usability score.

Is Kaggle difficult?

– It requires trust, an ethical orientation, and a cooperative mindset. Alternatively, placing high in a competition solo is widely regarded as one of the hardest things to do on Kaggle- in fact, in order to achieve Competitions Grand Master status you must have achieved a solo gold, and 5 gold medals total.

Is Kaggle a good way to learn data science?

Kaggle can be a great way for newcomers to build data science skills. At a certain point, though, its artificial nature and emphasis on competition become harmful. Developer and writer currently exploring the depths of machine learning and augmented reality on mobile.

What is Kaggle and why should you use it?

This data is real and referenced, so you can train and test your models on projects that could eventually help real people. There are plenty of other useful features of Kaggle like data, code, community, inspiration, competition, and courses. I will detail these benefits down below so that you find some helpful use out of Kaggle.

Is there a list of datasets for Kaggle?

There are several datasets for use on Kaggle. Here [4], you can see a list of datasets, as well as search by name for specific datasets that can be ingested in your future data science model. Most of the datasets are in CSV file format.

Is Kaggle’s leaderboard addictive?

The truth is, making the top 0.1 percent on Kaggle’s leaderboard isn’t a cakewalk, no matter how good you are. This addiction to improving model accuracy for a better ranking might be a good move from Kaggle to gamify data science and keep people coming back, but it’s freakishly addictive and not that beneficial for data scientists themselves.