The picture above,taken from Microsoft’s free introduction to machine learning course, available on github, succinctly expresses how the concepts relate to one another.
Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Data Science are related but distinct fields in computer science that involve different techniques and applications.
AI refers to the ability of machines to perform tasks that would normally require human intelligence. These include activties such as visual perception, speech recognition, decision-making, and natural language processing. AI is a broad field that encompasses a range of techniques and applications, including rule-based systems, expert systems, neural networks, and evolutionary algorithms.
Machine Learning (ML) is a subfield of AI that involves developing algorithms that can learn from and make predictions using data. Rather than being programmed directly with explicit rules, ML algorithms learn patterns and relationships in data through experience and iteration. Examples of ML algorithms include decision trees, random forests, and support vector machines.
Deep Learning (DL) is a subset of ML that involves training deep neural networks, which are complex mathematical models inspired by the structure and function of the human brain. DL has enabled breakthroughs in areas such as computer vision, natural language processing, and speech recognition. Examples of DL algorithms include convolutional neural networks, recurrent neural networks, and generative adversarial networks.
Data Science is a broader field that involves extracting insights and knowledge from data using a combination of statistical analysis, machine learning, and domain expertise. Data scientists use techniques such as data mining, data visualization, and predictive modeling to extract actionable insights from data. Data science has applications in a wide range of fields, including healthcare, finance, marketing, and social science.
In summary, AI refers to the broader goal of creating machines that can perform human-like tasks, while machine learning and deep learning are specific techniques for achieving that goal. Data science is a broader field that involves using statistical analysis and machine learning to extract insights and knowledge from data.