What is the difference between AI, Machine Learning, and Deep Learning ?

 

1. Artificial Intelligence (AI)

• Definition: AI is the broadest concept. It refers to machines or systems that can perform tasks that typically require human intelligence, such as reasoning, problem-solving, understanding language, and decision-making.
• Goal: To create systems that mimic human cognitive functions.
• Examples:
  • Chatbots
  • Recommendation systems
  • Autonomous vehicles

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2. Machine Learning (ML)

• Definition: ML is a subset of AI that focuses on algorithms that allow machines to learn from data and improve performance over time without being explicitly programmed.
• Key Idea: Instead of hardcoding rules, ML models learn patterns from historical data.
• Examples:
  • Spam email detection
  • Predictive analytics
  • Fraud detection

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3. Deep Learning (DL)

• Definition: DL is a subset of ML that uses artificial neural networks with multiple layers (hence "deep") to model complex patterns in large datasets.
• Key Idea: It excels in tasks like image recognition, speech processing, and natural language understanding because it can automatically extract features from raw data.
• Examples:
  • Face recognition
  • Voice assistants (like Siri, Alexa)
  • Self-driving car vision systems

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Hierarchy Visualization

AI → ML → DL

• AI is the umbrella term.
• ML is one approach to achieve AI.
• DL is a specialized technique within ML.