What are the two common classes of machine learning models?
- Supervised ML models
- Unsupervised ML models
The key difference is that supervised models use labeled data while unsupervised models use unlabeled data.
In supervised learning, what type of data is used?
Labeled data
Labeled data comes with tags like a name, type, or number.
In unsupervised learning, what type of data is used?
Unlabeled data
Unlabeled data comes with no tags.
What is an example of a problem that a supervised model might solve?
Predicting future tip amounts based on total bill amount
The model learns from past examples to make predictions.
What is an example of a problem that an unsupervised model might solve?
Grouping or clustering employees based on tenure and income
Unsupervised problems focus on discovery and natural groupings in raw data.
In supervised learning, what happens to the predicted values during training?
The model tries to reduce error between predicted and actual values
This is a classic optimization problem.
What is the main focus of unsupervised learning?
Discovery of natural groupings in data
It involves looking at raw data to see if it falls into groups.
What is the relationship between deep learning and machine learning?
Deep learning is a subset of machine learning methods
It represents a more advanced approach within the broader field.
