Notes of IBM Artificial Intelligence Analyst Course
This is a "Question and Answer" application built using IBM watsonx.ai flows engine. The project leverages a vector database to enhance the Large Language Model's (LLM) context awareness with a set of documents, specifically watsonxdocs.
Reference Kubernetes demos for AI agents and RAG: deploy containerized agent services, optional Qdrant vector store, FastAPI endpoints, and integrations for MLflow tracking, Evidently monitoring, and governance (non‑root images, SBOM, scans).
AI-powered Emotion Detection System built with Flask, utilizing Watson NLP API and NRCLex fallback for sentiment analysis.
The GitHub repository showcases completion of IBM courses on AI and Python. Topics cover AI fundamentals, generative AI, chatbot development, Python for data science, and AI application with Watson APIs, detailing key lessons and practical projects.
Detect the emotion behind a piece of text
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