A Recursive AI Chatbot with Dynamic Response

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prerequisites
Intermediate Python • basic data handling • willingness to read docs
skills learned
Recursive query handling • Dynamic programming for caching • Sentiment and fuzzy matching • NLP-based intent detection
Ronnie Rahman
1 week · 4-6 hours per week · INTERMEDIATE
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A client’s online support system is failing to meet customer expectations, and you’ve been brought in to elevate their chatbot into something more intelligent and responsive. You’ll overhaul the system using recursive and dynamic programming techniques to enable complex query handling and efficient memory caching. You’ll also integrate NLP techniques like sentiment analysis and fuzzy matching to better interpret user intent, all while retrieving responses from the SQuAD dataset. You’ll soon have a seamless chatbot ready for deployment in modern customer service environments.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Ronnie Rahman
Ronnie Rahman is a Senior Software Developer and an AI engineer with ilem Group in Casablanca in collaboration with Swisstiming in Switzerland where he delivers algorithm-driven software for digital-transformation projects. He earned a BSc (Hons) in Computer Science in AI from the University of Hertfordshire, concentrating on neural networks, robotics, quantum computing, and AI algorithms. A frequent speaker at regional Python and data-science meet-ups, he contributes to open-source performance tools and mentors developers on writing efficient and explainable code.

prerequisites

This liveProject is aimed at Python programmers interested in turning theoretical algorithms into a portfolio of practical applications. To begin you will need to be familiar with:


TOOLS
  • Intermediate Python
  • Basic JSON
  • Intermediate algorithms and data structures

TECHNIQUES
  • Recursive problem solving
  • Dynamic programming
  • Natural language processing

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