Kaggle has allowed companies to utilize the many people around the world interested in data to solve real world problems
This has opened up new opportunities for people to dive into data science wherever they may be, and companies have access to utilize this newfound interest to solve their own problems.
With merely an internet connection and access to a programming language, people around the world can compete in these competitions alone, or with others thousands of miles away.
Kaggle has given these companies the ability to connect with intelligent and inquisitive people from around the world that they most likely would have never come into contact with. No longer do these companies have to rely on their own employees to solve problems or improve their products. They can turn to the vast network that is the Internet to improve products.
Kaggle allows connections between one-to-many, many-to-one, many-to-many, and one-to-one.
During a competition, data is provided through Kaggle, and anyone with a Kaggle account can access the data and compete. This is a one-to-many connection as this data is uploaded with the purpose of being accessed by thousands.
Kaggle has a vast community of knowledgeable individuals that are constantly interacting with one another either through many-to-many connections such as through forums, or through one-to-one connections with individuals connecting with one another.
People who compete in teams must collaborate with one another, and this can be done through a one-to-one connection or a many-to-many connection for larger teams.
People can interact through several platforms, such as on forums or social messaging. Kaggle has forums for people to ask questions and receive help from fellow competitors.
Kaggle competitions take advantage of algorithmification, especially machine learning, as competitors try to create the best predictive model for the given data.
Kaggle competitions consist of creating the best predictive model given a dataset and a problem that accompanies the dataset. It is highly unlikely to create the best model without utilizing machine learning.
Machine learning is the result of an algorithm learning from the data and creating the best model that leads to the best predictions. This may be through random forests, as seen in the image from the right taken from a Kaggle dataset whose goal was to predict those on the Titanic that were most likely to survive.
Kaggle itself utilizes their own algorithms to score the models and decide who has the best model. This would be incredibly time-consuming to score thousands of models by hand so Kaggle takes advantage of algorithmification to do it for them.
Improving the World One Algorithm at a Time
Kaggle has truly revolutionized crowd sourcing in the digital age. They have allowed companies to reach out across the world and connect with smart, inquisitive people to help solve issues or improve products. Kaggle can upload data and watch magic unfold as thousands of people work to create efficient models to better existing technologies. Kaggle has worked with companies such as Netflix to improve their recommendations for customers, as well as NASA to map dark matter.
One example of the incredible effects Kaggle has had is the longest competition to date, The Heritage Health Prize. This three year competition allowed people to compete in creating an algorithm that predicts when people will be admitted to a hospital in an effort to prevent unnecessary and expensive hospitalizations. Unnecessary hospitalizations has cost billions of dollars each year. An algorithm that could successfully predict unnecessary hospitalizations would save billions of dollars.