Here’re the ten simplified meanings of Machine Learning Key Terms. Frankly, you always need these terms in memory. It’s no matter if you’re a working professional or Job searcher. ML solely a framework to solve real-life problems. Moreover, it provides insights. You may also like: Quiz on Machine Learning.
Machine learning key terms
| Word | Definition |
|---|---|
| 1. instance or example | A single object, observation, transaction, or record. |
| 2. target or label | The numerical or categorical (label) attribute of interest. This is the variable to be predicted for each new instance. |
| 3. features | The input attributes that are used to predict the target. These also may be numerical or categorical. |
| 4. model | A mathematical object describing the relationship between the features and the target. |
| 5. training data | The set of instances with a known target to be used to fit an ML model. |
| 6. recall | Using a model to predict a target or label. |
| 7. supervised machine learning | Machine learning in which, given examples for which the output value is known, the training process infers a function that relates input values to the output. |
| 8. unsupervised machine learning | Machine-learning techniques that don’t rely on labeled examples, but rather try to find hidden structure in unlabeled data. |
| 9. ML workflow | The stages in the ML process: data preparation, model building, evaluation, optimization, and prediction. |
| 10. online machine learning | A form of machine learning in which predictions are made, and the model is updated, for each new example. |
Also read: Google Cloud Certification
Supervised Vs. Unsupervised
| Instances (Examples) | M/F (Attribute-1) | Salary (Attribute-2) | Target (Label) |
|---|---|---|---|
| instance-1 | M | 10,000 | Eligible for Bonus |
| Instance-2 | F | 20,000 | Not Eligible for Bonus |
Here, the predictable value (Eligibility) is pre-defined. So, if you know the Target upfront, it is called Supervised Learning. In the case of unsupervised learning, the target is unknown; It is something to find hidden predictions.
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[…] Here, the ‘Y’ is the target. The F(X) is actual data. And, you can call ‘e’ as an error, which is not related the function F. The features list is X1, X2, X3…….Xn. Here is Machine learning terminology. […]
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