Machine Learning
Machine learning is a method that lets computers learn patterns from data instead of relying on hand-written rules.
Machine learning is a method that allows computers to find and learn patterns in data on their own, rather than having people program the rules one by one. Instead of having people write down rules to filter out spam emails, computers learn the characteristics of spam by showing them tens of thousands of spam emails.
It has been developed to solve complex problems that are difficult to write down with rules, such as facial recognition or demand forecasting. Recommendation systems, financial fraud detection, and search rankings are already incorporated into the services we use every day, and deep learning is also a branch of machine learning. You can understand it as a structure where machine learning is under the big umbrella called AI, and deep learning is within it.
Because the power of machine learning ultimately comes from data, if the data is biased, the results will also be biased. It is also important to note that it is vulnerable to situations outside the scope of learning as a basic limitation.
✅ Why it matters
- It is the basic concept that supports the entire modern AI and is the starting point for learning
- It allows you to solve complex problems that could not be solved with rules using data
- It helps you understand the operating principles of everyday services such as recommendations and searches
⚠️ Limits and debates
- Bias and errors in the data are reflected in the results
- Weak in new situations outside the scope of learning
- It is often difficult to explain why such judgments were made