If you've ever wanted to discover more about Kaggle, the online community for machine learning students and data scientist practitioners then look no further than our expert-led guide to get an overview on all the basics you need to know about this amazing opportunity provider and competition organiser.
What Is Kaggle?
For our first Kaggle overview, Alejandro Cantarero, PhD mathematician and CTO at Nami ML. kindly contributed his extensive thoughts on this topic below: “Kaggle is a website where companies post data science challenges. The platform provides a set of data and guidance for what they want you to do with each data set.”
“One of the most well-known examples of this type of competition was the Netflix Prize, though this was not hosted on the Kaggle platform.”
“Kaggle competitions can take a lot of time and effort and people usually participate in their free time. Winning solutions require a large time investment, and are often done by teams rather than individuals.”
“Why commit so much of your free time to a competition? Because it can help you land your first Data Science job.”
“Kaggle competitions are a chance to work with real-world data very similar to what you would encounter in a data science job. Working on a Kaggle problem and then sharing your solution publically on a service like GitHub can be a great way to get the attention of recruiters and hiring managers.”
“Winning solutions to Kaggle competitions are often very complex. More complex than the types of machine learning solutions most companies deploy into their products. Netflix used parts of the winning solution to the Netflix Prize, but they did not directly take the solution and add it to their app.”
“You do not have to build a winning solution to a Kaggle competition to help you land that first data science position. A good solution that shows you know how to work with the data is generally sufficient.”
Our second expert Olivia, co-founder of CocoFax, explained some of the origins of Kaggle and cited a few of their most notable achievements in her response: “Anthony Goldbloom (CEO) and Ben Hamner (CTO) founded Kaggle in 2010, and Google acquired the company in 2017.”
“Kaggle competitions have improved the current progress of machine learning in several areas. One is mapping dark matter; another is HIV/AIDS research. Looking at the winners of Kaggle competitions, you’ll see lots of XGBoost models, some Random Forest models, and a few deep neural networks.”
“In recruitment competitions, individuals compete to build machine learning models for corporation-curated challenges. At the competition’s close, interested participants can upload their resumes for consideration by the host. The prize is often potentially a job interview at the company or organization hosting the competition.”
How To Reference Kaggle Achievements On Your Resume:
Our next expert, Darshan Somashekar, Founder & CEO, Freecell-Challenge, generously contributed his insights on how aspiring machine learning and data science professionals can reference Kaggle on their CV or resume.
“Beginner data scientists can take on Kaggle challenges, comprehend the data, and submit their forecasts to Kaggle in a predetermined format.”
“They'll check your predictions and give you a score and a ranking. Users fight for the top rankings, which change frequently as people refine their predictions and submit them many times to the site.”
“You will be rewarded with incentives, including a cash prize if your predictions are the most accurate. This is one method of interacting with the platform.”
“The second approach to utilize Kaggle is to train machine learning algorithms on datasets that have already been released (years/months ago). You can submit your predictions to the site, and thousands of others will do so as well.”
“You'll be among the first few individuals on the scoreboard if your predictions reach the top.”
“Kaggle Grandmasters are usually dedicated data scientists and researchers who enjoy competing, and earning one requires a lot of effort and inventiveness.”
“If you are in the top 5% of people who submit forecasts, it will lend extra credibility to your CV and let would-be employers know that you know what you're talking about when it comes to data science.”
“For Example, You can write Kaggle: Titanic dataset: top 5% in your resume.”
The Three Leading Uses For Kaggle
Eduardo Perez, Founder at Musician Authority provided the three ways that users can engage with Kaggle, whether they are students, experienced data science professionals or corporations below;
Kaggle provides an opportunity for aspiring data scientists to work on actual datasets while learning and practising data science.
Kaggle provides opportunities for data science practitioners to compete in, learn about, and win Data Science challenges from reputable organizations.
For businesses, Kaggle is a platform where they can identify the correct data science expertise as well as crowdsource current challenges to be solved by the world's best data scientists.
We hoped that you enjoyed this blog explaining what is Kaggle, why not check out another one of our blogs and learn more about canary deployment?