Answer / Nripendra Chandra Verma

The basics of machine learning include understanding algorithms, models, and techniques used to enable a computer system to learn from data and make predictions or decisions without being explicitly programmed. Key concepts include supervised learning (where the algorithm learns from labeled data), unsupervised learning (where the algorithm learns from unlabeled data), reinforcement learning (where an agent learns by interacting with an environment), and deep learning (which uses neural networks with many layers to model complex patterns).

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Can you explain what is the difference between inductive machine learning and deductive machine learning?

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