Basic technical FAQs on AI
When it comes to technical questions about AI, especially in interviews, discussions, or learning contexts, they often focus on foundational concepts, algorithms, implementation, and practical applications. Below is a list of frequently asked technical questions about AI, grouped by category, along with brief insights into what they’re probing. These are common in fields like data science, machine learning engineering, and AI research. Foundational Concepts What is the difference between AI, Machine Learning (ML), and Deep Learning (DL)? Tests understanding of AI as a broad field, ML as a subset using data-driven learning, and DL as a specialized ML technique with neural networks. What are supervised, unsupervised, and reinforcement learning? Assesses knowledge of the three main learning paradigms: labeled data (supervised), finding patterns without labels (unsupervised), and learning via rewards (reinforcement). What is overfitting, and how do you prevent it? Probes understandin...