🚀 AI Interview Questions with Answers (Part 13)
121. What is OpenCV, and what are its applications? OpenCV (Open Source Computer Vision Library) is an open-source library used for computer vision and image processing.
Applications: • Face detection and recognition • Object detection • Image filtering and enhancement • Motion tracking • OCR (Optical Character Recognition) • Video analysis • Autonomous vehicles
OpenCV supports Python, C++, and Java.
122. What is the Hugging Face Transformers library? Hugging Face Transformers is an open-source Python library that provides access to thousands of pre-trained Transformer models for NLP, computer vision, audio, and multimodal AI.
Popular models include: BERT, GPT, T5, Llama, Mistral
Benefits: • Easy-to-use APIs • Pre-trained models • Fine-tuning support • Integration with PyTorch and TensorFlow
123. What is LangChain, and how is it used in LLM applications? LangChain is an open-source framework for building applications powered by Large Language Models.
It helps developers connect LLMs with: Databases, APIs, Documents, Vector databases, External tools
Common use cases: AI chatbots, RAG applications, AI agents, Document Q&A, Workflow automation
124. What is LlamaIndex, and what problem does it solve? LlamaIndex is a framework that helps connect Large Language Models with private or enterprise data.
It simplifies: Data ingestion, Index creation, Retrieval, Querying documents
LlamaIndex is widely used in Retrieval-Augmented Generation (RAG) applications.
125. What is Ollama, and how is it used for running local LLMs? Ollama is a tool that allows users to download, run, and manage Large Language Models locally on their own computers.
Benefits: • Runs models offline • Better privacy • Lower latency • No API costs • Supports models such as Llama, Mistral, Gemma, and Phi
Used for local AI development and experimentation.
126. How do you use the OpenAI API in AI applications? The OpenAI API enables developers to integrate AI capabilities into applications.
Common use cases: Chatbots, Content generation, Code generation, Text summarization, Translation, Image generation, Speech-to-text, Text-to-speech
Developers send prompts through API requests and receive AI-generated responses.
127. How do you use the Anthropic API for LLM development? The Anthropic API provides access to Claude models for building AI-powered applications.
Used for: Conversational AI, Document analysis, Content generation, Coding assistants, Enterprise AI applications
Supports long-context processing and emphasizes safe and reliable AI interactions.
128. How do you use the Google Gemini API in AI projects? The Google Gemini API allows developers to integrate Gemini models into applications.
Capabilities: Text generation, Image understanding, Code generation, Document analysis, Multimodal AI, Question answering
Supports applications that combine text, images, audio, and other data types.
129. What is MLflow, and why is it important in MLOps? MLflow is an open-source platform for managing the complete Machine Learning lifecycle.
Features: Experiment tracking, Model packaging, Model registry, Model deployment, Version control
MLflow improves collaboration, reproducibility, and deployment of ML models.
130. What is Weights & Biases, and how is it used for experiment tracking? Weights & Biases (W&B) is an MLOps platform used to track, visualize, and manage Machine Learning experiments.
Features: Experiment tracking, Hyperparameter tuning, Model monitoring, Dataset versioning, Performance visualization, Team collaboration
Helps data scientists compare experiments and improve model performance more efficiently.
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