Comprehensive AI/ML and LLM interview questions covering fundamental concepts, algorithms, and practical applications. AI/ML Fundamentals Interview questions covering core machine learning concepts, algorithms, and best practices: Easy: Supervised/unsupervised learning, overfitting, bias-variance tradeoff, basic …

Easy-level AI/ML interview questions with LangChain examples and Mermaid diagrams. Q1: What is the difference between supervised and unsupervised learning? Answer: graph TB subgraph Supervised["🎯 Supervised Learning"] A1[Labeled Data<br/>X, y pairs] --> B1[Train Model] B1 --> C1[Predict y<br/>for new X] style A1 …

Practical recipes for building LLM applications with LangChain: prompts, chains, agents, memory, and RAG. Installation 1# Core LangChain 2pip install langchain langchain-community langchain-core 3 4# OpenAI 5pip install langchain-openai 6 7# Other providers 8pip install langchain-anthropic # Claude 9pip install …

Simple stdin chatbot using LangChain with tool calling (OpenRouter). Installation 1pip install langchain langchain-openai python-dotenv Environment Setup 1# .env 2OPENROUTER_API_KEY=your_api_key_here 3OPENROUTER_MODEL=openai/gpt-4-turbo-preview Basic Chatbot 1import os 2from dotenv import load_dotenv 3from …