How Data Scientists Use Embeddings for Search

Lucas and Luna explore how data scientists are using embeddings to transform search. From semantic understanding to handling typos and synonyms, they unpack the shift from keyword matching to meaning-based retrieval. With a practical case study on Wikipedia's search overhaul, they discuss the challenges of scaling embeddings, the importance of evaluation, and how generative AI is changing the game. If you've ever wondered what powers the search bar in your favorite app, this episode breaks it down. #Embeddings #Search #DataScience #MachineLearning #VectorSearch #SemanticSearch #Wikipedia #NLP #Technology #Business #FexingoBusiness #BusinessPodcast #DataPodcast #AI #DeepLearning #RecommendationSystems #InformationRetrieval #DataEngineering Keep every episode free: buymeacoffee.com/fexingo