In the previous post, we saw the first two types of machine learning. In this post, we will discuss the other two types of machine learning. These are — Semi-su - machinelearning python
, we saw the first two types of machine learning. In this post, we will discuss the other two types of machine learning. These are — Semi-supervised machine learning and Reinforcement learning.This type of learning is new and is an important part of the machine learning field. We use this type of learning when we have some labeled data and many unlabelled data in training. This type of learning is in between supervised and unsupervised learning.
Thus, situations may arise where we have a small amount of labeled data and a large amount of unlabeled data. Then in such cases, we can neither go to a supervised nor unsupervised learning strategy. So, in such cases, semi-supervised learning comes to our rescue. We can significantly increase our accuracy and save time and effort in labeling every data point.
The central concept is to cluster different data points in the same clusters and then use supervised learning to name data points or instances in those groups. This usage of this type of learning is when we don’t have any data to start. In Reinforcement learning, the agent begins executing the tasks, and if he does the tasks correctly, the agent gets rewarded, and if he makes a mistake, he gets punished. Like in the above example, Increment in the score is a reward, and a decrement in the score is punishment.
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