what is machine learning

Machine learning

 is when a computer iteratively learns from data and finds hidden patterns. Then, by applying the learned results to new data, the future can be predicted according to the pattern. Algorithms implemented by manual programming can be automatically constructed from a large amount of data, so they are applied in various fields.

Machine learning iteratively "learns" from data using a variety of algorithms, allowing computers to autonomously derive insights from the data without explicitly programming where humans should look. 

Evolution of machine learning

With the advent of new computing technology, machine learning today is different from what it used to be. Machine learning was originally born from pattern recognition and the theory that computers can learn without being programmed to perform specific tasks. Researchers interested in artificial intelligence began to wonder if computers could "learn" from data. The "repetitive" aspect of machine learning is important. This is because the model adapts autonomously as it processes new data.

The results learned by the model are used to make reliable and reproducible decisions and the results.

This science isn't that new, but it's gaining new momentum right now.

Many machine learning algorithms have existed for many years, but it is the technology of recent years that has made it possible to automatically and ultra-fastly apply complex numerical calculations to big data over and over again. Thanks to the development.

Below are some of the widely published application examples of machine learning. You may already know some of them.

• Google's robot car (self-driving car) that is widely advertised. The essence of machine learning is there.
• Recommendation function of online shops such as Amazon and Netflix. This is an example of machine learning applied in daily life.
• Know what your customers are tweeting about your company on Twitter. Judgment is made by combining machine learning and language rules.
• Fraud detection. It is one of the clear and important uses of machine learning in today's society.

Why machine learning is important

The renewed interest in machine learning is for the same reason that data mining and Bayesian analysis have become more common than before. The available data continues to grow and its form is diversifying. In addition, the processing power of computers is becoming cheaper, and the cost of data storage is becoming lower.

As a comprehensive result of these factors, it has become possible to automatically generate "a model that can analyze a large amount of complex data and provide more accurate results more quickly" in a short time, and can handle extremely large data. It came to be. Building an accurate model also opens up opportunities for businesses and organizations to identify revenue-generating opportunities and avoid unknown risks.