6. What Is Machine Learning

Machine learning is a subfield of artificial intelligence that build a mathematical model of data to help understand data. By giving tunable parameters to the model which can be adapted to observed data, learning occurs. Once the model has been fit to previously observed data, it can predict based on new observed data.

Categories of Machine Learning

Machine learning problems can be categorized into two main classes:

Supervised learning build a relationship between measured features and some labels associated with the data. This category is subdivided into classification with discrete labels ans and regression with continuous labels.
Unsupervised learning build the model of data without considering any labels involved in the the data. This is the concept of "letting the dataset speak for itself". Unsupervised learning is subdivided to clustering and dimensionality reduction tasks. Clustering algorithms put the observed data in different categories while the dimensionality reduction techniques are provided to find more efficient repersentations of the data.

There is also semi-supervised learning which falls between supervised and unsupervised methods.

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