Building SMART Recommendation Systems in Python

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Building SMART Recommendation Systems in Python

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    By Arthur Kakande

    AI Developer at Pollicy

    Abstract:

    “intellikit” is a Python package for Case-Based Reasoning (CBR) and Information Retrieval (IR). During this workshop participants will be introduced to CBR (an AI technique that enables information managers to increase efficiency and reduce costs by substantially automating processes such as diagnosis, scheduling, and design). Join us for an immersive workshop where you’ll delve into the world of case-based reasoning (CBR) and learn how to harness this powerful technique to create intelligent information systems. Case-based reasoning is a problem-solving methodology that relies on past experiences (cases) to guide future decision-making. A case-based reasoner works by matching new problems to “cases” from a historical database and then adapting successful solutions from the past to current situations. Organizations as diverse as IBM, VISA International, Volkswagen, British Airways, and NASA have already made use of CBR in applications such as customer support, quality assurance, aircraft maintenance, process planning, and decision support, and many more applications are easily imaginable. It is relatively simple to add CBR components to existing information systems. Throughout the workshop, you will:

    • Understand the fundamentals of CBR and its applications in building intelligent systems (Specifically recommendation systems).
    • Learn how the various approaches to building recommender systems work. (Content-based, collaborative-filtering, knowledge-based)
    • Learn how to use the “intellikit” Python package to develop prototype systems that can reason and adapt based on past experiences.
    • Explore real-world examples of intelligent systems built using CBR such as Pollicy’s hospital recommendation system for hospital facilities in Uganda.

    This workshop is ideal for data scientists, software engineers, and anyone interested in developing adaptive and intelligent systems using Python. By the end of the session, you’ll have the skills to start building your own AI systems powered by case-based reasoning.

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