Embeddings: The Foundation of Modern AI 🧠

What are embeddings? A Book Review

“What are Embeddings? by Vicki Boykis”

What are Embeddings? is a comprehensive book written by Vicky Boykis under a Creative Commons license. The book provides a deep dive into the concept of embeddings.

Embeddings are a way of transforming data into numerical vectors that can be used as input to deep learning models.

They can capture the semantic meaning of data such as words, images, or products, and are widely used in applications such as natural language processing, computer vision, and recommender systems.

The author Vicky Boykis covers the history, usage, and challenges of embeddings in various domains, such as natural language processing, computer vision, and recommender systems.

The most valuable aspect of the book is that it introduces some of the most popular and influential embedding methods, such as Word2Vec, BERT, GPT, and Transformers, and explains how they work and what they can do.

In addition, this book discusses how embeddings are used in production systems, such as Pinterest, YouTube, and Twitter, and what are the engineering problems and best practices for managing embeddings at scale.

This is the best resource I have found so far for anyone interested in the applications of embeddings in machine learning and data science.