AI, Machine Learning, and Deep Learning
One of the most common questions I still see is:
“What’s the difference between AI, Machine Learning, and Deep Learning?”
These terms are often used interchangeably, but they are not the same. Understanding the distinction early can save a lot of confusion—especially for students and early-career professionals entering the AI space.
A simple mental model 
Artificial Intelligence (AI)
The broad umbrella. AI refers to any system designed to mimic human intelligence—such as reasoning, decision-making, problem-solving, and planning.
Machine Learning (ML)
A subset of AI where systems learn patterns from data instead of being explicitly programmed. This includes supervised, unsupervised, and reinforcement learning.
Deep Learning (DL)
A subset of Machine Learning that uses multi-layer neural networks. Deep Learning powers image recognition, speech processing, natural language understanding, and modern Generative AI models.
Why this distinction matters:
• Helps you decide what to learn next
• Clarifies job roles and expectations
• Makes interviews and technical discussions easier
• Prevents confusion when entering AI/ML fields