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Tag: NLU

  • Agentic AI Explained (Detailed)

    Agentic AI Explained for Novices (Detailed) Imagine a future where AI systems are not just tools waiting for your commands, but intelligent entities that can proactively understand your goals, plan their own actions, and work autonomously to achieve them. This is the vision of Agentic AI, a paradigm shift in artificial intelligence that moves beyond… Read more

  • Use Cases: Enhancing Customer Experience and Business Operations with Data Science

    Enhancing Customer Experience and Business Operations with Data Science Enhancing Customer Experience and Business Operations with Data Science Data science provides powerful tools to understand customers better, personalize their experiences, and optimize core business operations. This article explores ten key use cases in these areas. 1. Customer Churn Prediction Domain: Customer Relationship Management (CRM), Telecommunications,… Read more

  • Vector Embeddings in LLMs: A Detailed Explanation

    Vector Embeddings in LLMs: A Detailed Explanation What are Vector Embeddings? Vector embeddings are numerical representations of data points, such as words, phrases, sentences, or even entire documents. These representations exist as vectors in a high-dimensional space. The key idea behind vector embeddings is to capture the semantic meaning and relationships between these data points,… Read more

  • Building Agentic AI Applications on Google Cloud Platform (GCP)

    Google Cloud Platform (GCP) offers a rapidly evolving suite of tools and services for building agentic AI applications – intelligent systems capable of autonomous action, planning, memory, and interaction with their environment. Here’s a detailed overview of key GCP services and concepts, along with relevant links, formatted for your WordPress site. Core Foundation Models Agent… Read more

  • Building an AI Chatbot for Order Status with React.js, Rasa, and Flask

    This article details the development of an AI Chatbot that enables users to inquire about the status of their orders. The implementation utilizes a modern frontend built with React.js, a robust Natural Language Understanding (NLU) and dialogue management framework powered by Rasa, and a simple backend using Python (Flask) to serve order information. I. Core… Read more