This Talk will cover how to build Context-Aware Recommendation Systems using both text and image data. We will explore techniques to extract context from textual content, such as user posts or reviews, and visual content, like images shared by users. By integrating these diverse context sources into recommendation algorithms, we can significantly enhance the relevance and personalization of recommendations.

Participants will engage in hands-on implementation, utilizing NLP tools for text and computer vision techniques for images through Python and Keras. By the end of the session, you’ll be equipped to create robust, context-aware recommendation systems that leverage text and image data to drive user engagement. 

Key Takeways - Understand the principles of context-aware recommendation systems - Learn basic techniques for extracting context from textual content using NLP - Discover how to analyze visual content using computer vision methods - Gain insights into integrating text and image features for enhanced recommendations