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Artificial Intelligence and Machine Learning

Definition

Artificial Intelligence (AI) refers to the development of computer systems capable of performing tasks that typically require human intelligence, such as speech recognition or decision-making. Machine Learning (ML), a subset of AI, involves training algorithms on large datasets to make predictions or take actions without being explicitly programmed.

Analogy

Think of AI as a robot assistant that can understand your voice commands, perform complex calculations instantly, and even predict your needs based on patterns it has learned over time. Machine learning is like teaching this robot assistant how to improve its performance by showing it examples and letting it learn from experience.

Related terms

Neural Networks: Neural networks are computational models inspired by the structure and function of biological neural networks in the brain. They are widely used in machine learning for tasks such as image recognition or natural language processing.

Deep Learning: Deep learning is a subfield of machine learning that focuses on training deep neural networks with multiple layers. It enables more complex representations and higher accuracy in solving intricate problems.

Data Mining: Data mining involves extracting useful information or patterns from large datasets using various techniques such as statistical analysis or machine learning algorithms. It plays a crucial role in AI and ML by providing valuable insights for decision-making processes.