Chapter 1: Understanding Data Segmentation
Machine learning has two types of algorithms depending on the level of adjustments that you require to give a response:
- Supervised
- Unsupervised
Supervised algorithms need continuous improvement in the form of the data used to train them. For example, a supervised machine learning function of a linear model needs a starter group of data to train and generate the initial conditions. Then, we have to test the model and use it. We need continuous surveillance of the results to interpret whether they make sense or not. If the model fails, we probably need to train the model again.
Unsupervised algorithms do not require any previous knowledge of the data. The unsupervised machine learning process takes ...
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