Introduction¶
Definition¶
There are several definition of Machile learnings:
Arthur Samuel (1959)
The field of study that gives computers the ability to learn without being explicitly programmed.
Tom Mitchel (1998)
A computer program is said to learn from experience E with respect to some class of task T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E
Types of ML¶
In ML, there are three algorithms:
Supervised learning¶
Point
“Right answers” are given
Types
Regression (Link)
Classification.
Regression¶
Map input variables to some continuous functions to predict results within a continuous output
Example: Housing price prediction
Classification¶
Map input variables into discrete categories to predict results within a discrete output
Example: Breast cancer or Test grade (A, B, C, D, F)
Unsupervised learning¶
Point
Allow us to approach problems with little or no idea what our results should look like
Derive the structure from data where we don’t necessarily know the effect of the variables
No feedback based on the prediction results
Types
Clustering
Non-clustering