Simply put, machine learning is the link that connects Data Science and AI. That is because it's the process of learning from data over time. So, AI is the tool that helps data science get results and solutions for specific problems. However, machine learning is what helps in achieving that goal. Machine learning is a process in which the trained model (after learning from the historical data) starts making human-like decisions. In comparison, AI is the final state when your software mimics human intelligence, including the reasoning of those decisions. source (developed by the Author) Let me throw one more sentence to help you. Artificial Intelligence is a technology designed to make calculated decisions. Machine Learning is a subset of Artificial Intelligence that refers to the engineering aspects of AI. Under the umbrella of Machine Learning are a variety of topics, such as: The different maths used to predict AI's outcomes. Data collection and labelling. Artificial intelligence, machine learning and deep learning are easily confused. This infographic breaks down the differences between the three. Artificial intelligence (AI), machine learning (ML) and deep learning (DL) have expanded greatly in the past few years, and are predicted to keep growing in reach. The key distinction between AI and machine learning is that AI is designed to learn and improve on its own, whereas machine learning is designed to perform specific tasks for specific users. AI is better suited for tasks requiring intelligence because it is better suited to understand human speech and recognize objects. Artificial Intelligence refers to a science where a non-natural element can be made intelligent. In simpler terms, an artificial object, man-made object can understand and think on its own. Machine Learning Machine learning refers to ways by which a machine can learn without being programmed. Machine learning produces predictions Artificial intelligence produces actions To be clear, this isn't a sufficient qualification: not everything that fits each definition is a part of that field. (A fortune teller makes predictions, but we would never say that they are doing machine learning.) Understanding the difference between common buzzwords allows for productive conversations. Here are some buzzwords that are commonly conflated: Artificial Intelligence: A machine with any type of intelligent behavior. Machine Learning: A part of artificial intelligence that learns by itself Machine Learning — An Approach to Achieve Artificial Intelligence Spam free diet: machine learning helps keep your inbox (relatively) free of spam. Machine learning at its most basic is the practice of using algorithms to parse data, learn from it, and then make a determination or prediction about something in the world. Deep learning is one of many approaches to machine learning. Other approaches include decision tree learning, inductive logic programming, clustering, reinforcement learning, and Bayesian networks 1. Artificial intelligence has different types like reactive machines; the system only reacts, does not have the memory like the washing machine. Machine learning enables a machine to