1. Machine Learning
• Limitations of explicit programming
- Spam filter: many rules
- Automatic driving: too many rules
• Machine learning: "Field of study that gives computers the ability to learn without being explicitly programmed” Arthur Samuel (1959)
2. Supervised/Unsupervised learning
• Supervised learning:
- learning with labeled examples - training set
• Unsupervised learning: un-labeled data
- Google news grouping
- Word clustering
3. 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
4. Types 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, E and F) based on time spent
- multi-label classification
출처 : https://www.youtube.com/channel/UCML9R2ol-l0Ab9OXoNnr7Lw
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