Building Multi-Modal & Agentic AI on Azure: A Step-by-Step Approach

Artificial Intelligence 

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Machine Learning 

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Deep Learning 

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Data Science

AI (Artificial Intelligence) is a broad field that encompasses various subfields and

 technologies, such as machine learning (ML) and deep learning (DL).

• AI (Artificial Intelligence) is a broad field that encompasses the development of intelligent systems and software that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language understanding.

• ML (Machine Learning) is a subset of AI that focuses on the development of algorithms and statistical models that enable systems to learn from data, improve their performance over time, and make predictions or decisions without being explicitly programmed.

• DL (Deep Learning) is a subset of ML that uses neural networks with multiple layers to model complex patterns in data. It is particularly useful for tasks such as image and speech recognition, natural language processing, and decision making.

• Data Science is an interdisciplinary field that involves the extraction of insights and knowledge from data using a combination of tools and techniques from statistics, machine learning, and computer science. Data scientists use various methods like descriptive, inferential and predictive statistics, ML and DL to uncover the insights from the data and provide recommendations to the organizations.

In summary, AI is the broad field that encompasses everything, ML is a subset of AI that focuses on learning from data, DL is a subset of ML that uses neural networks, and Data Science is an interdisciplinary field that uses a combination of tools and techniques to extract insights from data.