Table 3.
Machine learning | Science of getting machines to interpret, process and analyze data in order to solve real-world problems. Types – supervised, unsupervised, and reinforcement learning |
Deep learning | Process of implementing Neural Networks on high dimensional data to gain insights and form solutions. For example, face verification algorithm on Facebook, self-driving cars, virtual assistants like Siri, Alexa |
Natural language processing (NLP) | The science of drawing insights from natural human language in order to communicate with machines and grow businesses. For example, Twitter uses NLP to filter out terroristic language in their tweets, Amazon uses NLP to understand customer reviews and improve user experience |
Robotics | Branch of artificial intelligence which focuses on different branches and application of robots. For example, Sophia the humanoid is a good example of AI in robotics |
Expert systems | An AI-based computer system that learns and reciprocates the decision-making ability of a human expert. Eg. mainly used in information management, medical facilities, loan analysis, and virus detection |
Fuzzy logic | A computing approach based on the principles of ‘degrees of truth’ instead of the usual modern computer logic, that is Boolean in nature. For example, used in the medical fields to solve complex problems involving decision-making, used in automatic gearboxes, vehicle environment control |