Answer / Arjun Tyagi

Machine learning (ML) is a subset of Artificial Intelligence (AI), which refers to a system's ability to perform tasks that would normally require human-like intelligence. ML involves training algorithms to learn patterns in data, make decisions, and improve through experience without being explicitly programmed. AI encompasses broader concepts like knowledge representation, reasoning, natural language processing, and robotics.

What is the method to avoid overfitting?

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What measure how far the predictions are from the actual values in machine learning?

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What is the difference between Entropy and Information Gain?

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Explain the Algorithm Technique of Reinforcement Learning in Machine Learning?

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Is macbook good for machine learning?

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Why is manhattan distance not used in knn machine learning algorithm to calculate the distance between nearest neighbors?

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Tell us an example where ensemble techniques might be useful?

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What is symbolic reasoning?

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Explain me what is bayes' theorem? How is it useful in a machine learning context?

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What is a binary classification in machine learning?

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How does gaussian naive bayes work?

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Explain the topics in machine learning?

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