Reinforcement learning is an area of Machine Learning, It is about taking suitable action to maximize reward in a particular situation. It is employed by various software and machines to find the best possible behavior or path it should take in a specific situation. Reinforcement learning differs from the supervised learning in a way that in supervised learning the training data has the answer key with it so the model is trained with the correct answer itself whereas in reinforcement learning, there is no answer but the reinforcement agent decides what to do to perform the given task. In the absence of training dataset, it is bound to learn from its experience.
Recommender systems are one of the most common and easily understandable applications of big data. The most known application is probably Amazon’s recommendation engine, which provides users with a personalized webpage when they visit Amazon website.
Augmented intelligence is an alternative conceptualization of artificial intelligence that focuses on AI's assistive role, emphasizing the fact that it is designed to enhance human intelligence rather than replace it. The choice of the word augmented, which means "to improve," reinforces the role human intelligence plays when using machine learning and deep learning algorithms to discover relationships and solve problems.