Hands-On Web Scraping with Python

Reinforcement learning

Reinforcement learning is a part of ML that deals with taking necessary action in order to increase the reward for a particular situation. It employs several pieces of software and machines in order to find the best possible path for a specific situation.

Reinforcement learning is different from supervised learning. In supervised learning, training data is provided with a label, based on which it is trained. In the case of reinforcement learning, the reinforcement agent makes the decision to resolve the task that's been assigned to them.

There are two types of reinforcement learning:

• Positive reinforcement: Maximizes performance and sustains changes for a longer duration

• Negative reinforcement: Minimizes performance ...