🤖 AI and 🤖 ML are related but distinct fields within computer science that deal with creating intelligent machines capable of performing tasks that typically require human intelligence.

Notes

🤖 ML is a subset of 🤖 AI, focused on developing algorithms that learn patterns from data. 🤖 AI], however, encompasses a broader range of intelligence simulation techniques beyond just learning from data.

1. 🤖 AI is a broader, more encompassing field focused on creating intelligent machines that can perform variouscognitive tasks. AI aims to simulate human intelligence in computers by combining aspects such as:
   • Learning: Acquiring information and rules for using the information.
   • Reasoning: Using the rules to reach approximate or definite conclusions.
   • ProblemSolving: Finding effective means of achieving goals.
   • Perception: Understanding and interpreting data from the environment through sight, sound, touch, etc.
2. 🤖 ML is a subset of AI focused on developing algorithms that allow computer programs to "learn" from data without being explicitly programmed.
   1. In other words, ML enables systems to improve their performance on a specific task over time bylearning patterns from historical data.
   2. There are three primary types of machine learning:
      • Supervised Learning: fromlabel ‘ed examples (input-output pairs) to make predictions or decisions
      • Unsupervised Learning from unlabel ‘ed data to find hidden patterns and relationships.
      • 🏆 Reinforcement Learning through trial and error by receiving rewards or penalties for actions taken.

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