Browse through our curated collection of machine learning interview questions.
What is agentic AI, and how does it differ from traditional AI in terms of function and design principles?
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How Large Language Models (LLMs) handle out-of-vocabulary (OOV) words or tokens?
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Can you explain how Large Language Models (LLMs) are typically trained? What are the key components and phases involved in their training process?
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Explain the different types of gradient descent algorithms and their trade-offs, highlighting their theoretical background and practical applications.
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Explain the differences between linear regression and logistic regression, focusing on their objectives, assumptions, and the types of problems they are best suited to solve.
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Can you explain the K-means clustering algorithm, including its step-by-step process, limitations, and practical applications? Additionally, when would K-means be the most appropriate choice for clustering data?
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