The Math of Cosine Similarity

Join us at our upcoming event on The Math of Cosine Similarity on Wednesday, November 19th at 6pm!

About the talk:
Join us for an enriching session on The Math of Cosine Similarity, where we’ll demystify one of the most powerful metrics in modern data science and machine learning. Whether you’re building a recommendation engine, working with text embeddings, or exploring vector-space models, understanding cosine similarity gives you the tools to compare, rank and retrieve high-dimensional data with confidence.

Seats are limited, make sure to save yourself a spot while they are still available!

About the Speaker:
Dev J. Shah is an Agile Software Engineer at TribalScale and GenAI evangelist based in Toronto. Dev is an active speaker in Toronto’s tech community. He frequently speaks at local meetups and events, where he shares insights on Retrieval-Augmented Generation (RAG) and other AI-driven disciplines. Beyond public speaking, Dev simplifies complex AI concepts through blogs and video content, helping developers not only understand emerging technologies but also apply them to build impactful, real-world projects.

Agenda:

​​​6:00 PM – Doors open
​​​6:30 PM – The Math of Cosine Similarity by Dev Shah
7:15 PM – Q&A
7:30 PM – Connect and clean up
8:00 PM – Wrap up

Who should attend:
This event is ideal for:

Data scientists and machine learning engineers who use embeddings or vector search.
Software developers curious about how high-dimensional comparisons work “under the hood”.
Students and researchers in NLP, information retrieval, recommender systems.
Technical managers and analysts who want to better understand the metrics that drive similarity-based systems.
Other technology enthusiasts!

Kindly note that all contents are subject to change

Agenda