Document Embeddings in Recommendation Systems

Talk by Jerry Chi, Data Science Manager at Indeed Tokyo.   / jerrychi   The talk includes: Brief overview of related concepts: Transformers, embeddings, and approximate nearest neighbors Using embeddings for retrieval vs. ranking Comparing production system architectures Comparing model architectures, fine-tuning vs. further pre-training Highlights of recent related research Meetup: https://www.meetup.com/Machine-Learni... ========================= MLT (Machine Learning Tokyo) site: github: https://github.com/Machine-Learning-T... slack: https://machinelearningtokyo.slack.co... discuss: https://discuss.mltokyo.ai/ twitter:   / __mlt__   meetup: https://www.meetup.com/Machine-Learni... facebook:   / machinelearningtokyo  

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