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Types of Learning in AI/ML/Neural Networks | Supervised, Unsupervised & Reinforcement Learning Explained 🤖

In this video, we break down the three main types of learning used in Artificial Intelligence (AI), Machine Learning (ML), and Neural Networks (NN) with simple language and real-life examples.

📌 What You’ll Learn:
🔹 Supervised Learning – Learn how machines are trained using labeled data.
🔸 Examples: Email spam detection, house price prediction
🔹 Unsupervised Learning – Understand how models find hidden patterns in unlabeled data.
🔸 Examples: Customer segmentation, anomaly detection
🔹 Reinforcement Learning – Discover how agents learn by interacting with an environment using rewards and penalties.
🔸 Examples: Game-playing AI, robotics, self-driving cars

✅ Also Covered:
✔️ Key differences between these learning types
✔️ Real-world applications and use cases
✔️ Simple diagrams and step-by-step explanation

By the end of this video, you’ll have a clear understanding of how machines learn from data, make decisions, and improve over time! 🌟

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