Kaggle

Kaggle; data scientists and those interested in machine learning is an online platform. It brings together data scientists and people interested in machine learning, and it's a large community.

Kaggle was founded in 2010 by Anthony Goldbloom and Jeremy Howard. Then, it was acquired by Google in 2017. With more than 8 million users, the purpose of Kaggle is to bring together those interested in data science, with the tools and resources it contains, to help them achieve their goals.

One of the best ways to improve data science and machine learning skills is by practice. The more real cases and datasets you encounter, the more you have the chance to improve yourself.

One reason why Kaggle is so popular among data scientists is that it includes competitions. As how important HackerRank is for developers, Kaggle is equally important for data scientists. You can take a look at the "Kaggle Competitions" here.

In our Datathons organized with company collaborations, data scientists of different levels compete using Kaggle. At the end of the Datathon, the people or teams who rank have the chance to win a grand prize.

Kaggle helps the users to cooperate with other users, publish datasets, and compete with other data scientists to solve the data science challenges.

Kaggle helps those starting a data science career to learn more about machine learning and develop their skills. In addition to these, it allows newcomers to follow industry trends.

What Can Be Done On Kaggle?

You can upload datasets to Kaggle. Even the datasets of other users can be downloaded and examined. Datasets and notebooks in these datasets can be checked. Discussion topics can be opened on these datasets.

All activities of the users on the platform are scored on Kaggle. The user settles in the score table as they get points. This score increases as more help is given to others and useful information is shared through Kaggle.

Kaggle is a free platform. All developers can examine the courses, datasets, dataset, competitions, and discussions on Kaggle.

Is Kaggle Score Important For Data Science Career?

Your Kaggle profile and score are quite important for your data science career. Mentioning your Kaggle experience has a positive impact on the interviews.

Whether you are a beginner or experienced developer, Kaggle offers continuous learning and development opportunities for all developers. And the grand prizes in the competitions are an extra advantage.

By winning Kaggle points and medals, you can show your skills in data science. Thus, you can draw attention to recruiters and managers and evaluate new job opportunities.

Is Kaggle a Good Way to Learn Data Science?

Of course, Kaggle is a platform that supports your data science learning process. It offers many opportunities to increase your knowledge and motivation.

Kaggle offers free course and certificate opportunities for beginner developers. Your motivation increases as your ranking increases on Kaggle, as you collect points from the competitions. You can learn about data science and machine learning trends by participating in exciting competitions. Kaggle supports various machine learning frameworks such as Caffe, Keras, Tensorflow, PyTorch and more.

Kaggle brings together developers interested in data science, machine learning, and artificial intelligence. By joining this platform, you can advance in a community of people with various levels of expertise and have the chance to communicate with many highly experienced data scientists. For example, you can ask a question about a code or data set and get help from other data scientists on the platform. This is a very instructive and useful practice, especially for beginners.

How Does Kaggle Work?

Each competition on Kaggle has a target you need to reach. These targets vary depending on the content of the competition. After submitting your prediction model for data, you cannot use your solution for future submissions.

What Are Kaggle Competitions?

Kaggle competitions consist of data science questions. Kaggle competitions are divided into different categories according to complexity levels, how long they last, cash prize and their topics .

The goal of competitions is to find the AI model that best fits the predetermined conditions. Each user submits their solution and ranked. Typically, there is a large prize at the end of these competitions. You can participate in these competitions alone or with your team.

In addition to the big prizes, you win points for medal and Kaggle score on the Kaggle platform. These points and medals are very important for your Kaggle profile. It both shows your ranking according to data scientists worldwide and also provides some advantages in your career process. Kaggle competitions can be anything from predicting housing prices, to prescribing approaches to definite CASE on “fault” or “outage” calls that could occur at the grid centres in the future.

How To Register For Kaggle?

Go to kaggle.com.
Click on the "Sign Up" button in the upper right corner.
Enter your email address and verify your account.

If you have just registered for Kaggle, you can learn the system by participating in competitions in the "Beginner" category. If you already have a Kaggle account, you can directly participate in the open competitions and show your skills in the field of data science.

At this point, you may be wondering how you can participate in Kaggle competitions. You can view all open competitions from the "Competitions" page.

When you click on the discussion tab, you will see many discussion topics related to the competitions. The discussion topic that receives the most votes is at the top, making it the winner of the competition.

What Is Kaggle Notebook? How Is It Used?

You can write your notes in the "Notebook" section on Kaggle. To save the notes, you need to click on the "Save Version" button in the upper left corner. Also, on Kaggle, you can review other users' notebooks.

What Skills Are Needed To Compete On Kaggle?

First and foremost if you want to participate in competitions, you should be confident in data analysis and machine learning. "Managing time correctly" is an important skill for Kaggle competitions that need to be solved within a certain period.

The ability to interpret data is also a must-have. Kaggle does not require machine learning and coding skills, but a good understanding of the basics of these topics will put you ahead of your competitors.

What Tools Can Be Used to Compete on Kaggle?

There is no coding knowledge requirement to use Kaggle, but most of those participating in Kaggle competitions are people who have improved themselves in the Python programming language.

More than 60% of all data scientists prefer the Python programming language.

In addition to these, tools like TensorFlow, R programming language, Git and Bash are also used by machine learning enthusiasts.