🔹 What Is Machine Learning?

Machine Learning (ML) is a field of Artificial Intelligence (AI) that focuses on teaching computers to learn from data and make decisions or predictions without being explicitly programmed.

Instead of following fixed instructions, ML systems find patterns in data and improve their performance over time as they are exposed to more information.

🔹 Key Idea

Traditional programming: Humans write explicit rules.

Machine Learning: The system learns rules automatically from examples (data).

💡 Example:

Traditional programming → Tell the computer: “If an email contains the word ‘lottery’, mark it as spam.”

Machine learning → Feed the computer thousands of spam and non-spam emails. The system learns patterns (words, sender, frequency) and predicts spam on its own.

🔹 Types of Machine Learning

Supervised Learning – Learns from labeled data (input + correct output).

Unsupervised Learning – Finds patterns in unlabeled data.

Reinforcement Learning – Learns by trial and error, guided by rewards.

🔹 Why Is It Important?

Machine learning powers many technologies we use daily:

Google Search → Learns what results are most relevant.

Netflix/Spotify → Recommends movies and songs.

Self-driving cars → Learn from sensor data to navigate.

Healthcare → Predicts diseases and helps in diagnosis.

✅ In short:

Machine Learning is about teaching computers to learn from data and make smarter decisions automatically.

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