Foundational Concepts: AI vs. Machine Learning vs. Deep Learning: What’s the Difference?

Artificial intelligence (AI) is a broad field of computer science that deals with creating intelligent agents, which are systems that can reason, learn, and act autonomously. Machine learning and deep learning are both subsets of AI, but they have different approaches to achieving intelligence.

• Artificial intelligence (AI) is the broadest concept of the three. It refers to the ability of a machine to mimic human cognitive functions, such as learning and problem-solving. AI can be achieved through a variety of methods, including machine learning and deep learning.
• Machine learning is a type of AI that allows computers to learn without being explicitly programmed. Machine learning algorithms learn from data, and they can be used to make predictions, classifications, and other decisions.
• Deep learning is a type of machine learning that uses artificial neural networks to learn from data. Artificial neural networks are inspired by the structure of the human brain, and they are able to learn complex patterns from data.

Here is a table that summarizes the key differences between AI, machine learning, and deep learning:

Each of these technologies has its own strengths and weaknesses, and the best approach for a particular technology will depend on the specific application. These technologies are all used in a variety of applications, from fraud detection to product recommendations to self-driving cars.

Future content please subscribe to: https://linktr.ee/madhumitamantri