The terms AI,ML,DL may sound all same and sometimes used interchangeably and often in confusing way.
Artificial Intelligence (AI): Represented by the largest oval, AI is the broadest concept. It refers to the simulation of human intelligence in machines that are programmed to think and act like humans. AI encompasses a wide range of applications, from problem-solving and learning to speech recognition.
Machine Learning (ML): Nested within AI, depicted by the middle oval, ML is a subset of AI focused on methods and algorithms that enable computers to learn from data. These systems improve their performance over time by learning from patterns in data, rather than being explicitly programmed for a specific task.
Deep Learning (DL): The smallest, innermost oval stands for DL. It is a more specialized subset of machine learning involving neural networks with multiple layers. These networks aim to replicate the human brain's decision-making process and can recognize patterns in various forms of data, leading to advancements in areas such as voice and image recognition.
This hierarchy visually clarifies that deep learning is a specialized form of machine learning, which itself is part of the broader field of artificial intelligence.