기본적인 Machine Learning의 용어와 개념 설명 - accidentlywoo/legacyVue GitHub Wiki

기본적인 Machine Learning의 용어와 개념 설명

---

Basic Concepts

• What is ML?
• What is learning? : supervised : unsupervised
• What is regression?
• What is classification?

Limitation of explict programming

• Spam filter : many rules
• Automatic driving : too many rules

Machine learning :

"Field of study that gives computers the ability to learn without being explictly programmed" Arthue Samuel(1959)

Supervised / Unsupervised learning

• Supervised learning : learning with labeled examples - training set
• Unsupervised learning : un-labeled data - Google news grouping - Word clustering

Supervised learning

• Most common problem type in ML : Image labeling : learning from tagged images : Email spam filter : learning from labeled (spam or ham) email : Predicting exam score : learning from previous exam score and time spent

Type of supervised learning

• Predicting final exam score based on time spent : regression
• Pass / Non-pass based on time spent : binary classification
• Letter grade (A, B, C and F) based on time spent : multi-label classification