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Best practices for autocomplete search
11 things to consider while implementing autocomplete search.
ML applications in retail and ecommerce
A short exploration of ML applications in retail and ecommerce.
What is Natural Language Processing (NLP)?
An overview of NLP, how it works and its applications.
What is multimodal search?
A brief overview of multimodal search, the challenges and drawbacks for retailers.
What is a vector database?
An overview of vector databases and how they work to power semantic search.
What is semantic search?
An overview of semantic search and brief guide on how to get started.
What is personalization?
An overview of personalization and how it can drive revenue for brands and retailers.
What is Retrieval Augmented Generation (RAG)?
An overview of RAG, how it works, and when to use it.
What is a Large Language Model (LLM)?
An overview of LLMs, how they work, their benefits and challenges.
How to generate embeddings
A step-by-step process on how to turn text into rich vector representations.
The lifecycle of an embedding
Learn about the lifecycle of embeddings from creation to optimization.
How do embeddings work?
Discover how embeddings work, the powerful technique transforming NLP.
What is an embedding?
A high-level overview of embeddings, how they work, and how to create them.
What is machine learning?
An overview of machine learning algorithms and how they are used today.
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