Basic of machine learning
TOC
Machine Learning
- Filed of study that gives computers the ability to learn without being explicitly programmed. - Arthur Samuel, 1959
Types of Machine Learning
- Supervised learning
- learning with labeled examples(training set)
- Classification
- Unsupervised learning
- learning with unlabeled data
- grouping and clustering
Supervised Learning
- Most common problems
- Examples:
- Object detection
- Email spam
- Prediction
Image 1. Object classification. (src: http://cs231n.github.io/classification/)
Types of Supervised Learning
- Regression
- Predicting final exam score based on time spent
| Hours | Score |
|---|---|
| 10 | 90 |
| 9 | 80 |
| 7 | ? |
| 3 | 50 |
| 2 | 30 |
Table 1. Prediction
- Binary classification
- Pass/non-pass based on time spent
| Hours | Score |
|---|---|
| 10 | PASS |
| 9 | PASS |
| 7 | ? |
| 3 | FAIL |
| 2 | FAIL |
Table 2. Binary Classification
- Multi-label classification
- Letter grade(A, B, C, D and F) based on time spend
| Hours | Score |
|---|---|
| 10 | A |
| 9 | B |
| 7 | ? |
| 3 | D |
| 2 | F |
Table 3. Multi-label Classification
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