The distinction in unsupervised learning from supervised learning, as it may have surmised the data will not contain any labels, and the module should attempt prospects and learn without a teacher.
The semi-supervised learning algorithm is a combination of supervised learning and unsupervised. The algorithms run individually. For example, start with creating a module that begins gathering unlabeled data that will be later processed and labelled. It can go to another module that is on supervised learning mode waiting for labelled data.
Supposing we have random data of a specific amount of people (Figure 03), The Algorithm will find the connection between each person in the data provided even though it is not labelled (Figure 04).
Reinforcement learning is different from other ways of learning. in this method used is called the agent, this agent will analyse the environment (dataset) and then it selects and performs actions, these actions if they are right, the agent get a reward, and the learning process keeps going. (Figure 05)You can support my content, and help me do more and more by becoming a Patron!