Overview

AI has acquired startling new language capabilities in just the past few years. Driven by rapid advances in deep learning, language AI systems are able to write and understand text better than ever before. This trend is enabling new features, products, and entire industries. With this book, listeners will learn practical tools and concepts they need to use these capabilities today. You'll understand how to use pretrained large language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; and use existing libraries and pretrained models for text classification, search, and clusterings. This book also helps you understand the architecture of Transformer language models that excel at text generation and representation; build advanced LLM pipelines to cluster text documents and explore the topics they cover; build semantic search engines that go beyond keyword search, using methods like dense retrieval and rerankers; explore how generative models can be used, from prompt engineering all the way to retrieval-augmented generation; and gain a deeper understanding of how to train LLMs and optimize them for specific applications using generative model fine-tuning, contrastive fine-tuning, and in-context learning.

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Jay Alammar is director and engineering fellow at Cohere (pioneering provider of large language models as an API). In this role, he advises and educates enterprises and the developer community on using language models for practical use cases). Through his popular AI/ML blog, Jay has helped millions of researchers and engineers visually understand machine learning tools and concepts from the basic (ending up in the documentation of packages like NumPy and pandas) to the cutting-edge (Transformers, BERT, GPT-3, Stable Diffusion). Jay is also a cocreator of popular machine learning and natural language processing courses on Deeplearning.ai and Udacity. Maarten Grootendorst is a senior clinical data scientist at IKNL (Netherlands Comprehensive Cancer Organization). He holds master's degrees in organizational psychology, clinical psychology, and data science, which he leverages to communicate complex machine learning concepts to a wide audience. With his popular blogs, he has reached millions of readers by explaining the fundamentals of artificial intelligence-often from a psychological point of view. He is the author and maintainer of several open-source packages that rely on the strength of Large Language Models, such as BERTopic, PolyFuzz, and KeyBERT. His packages are downloaded millions of times and used by data professionals and organizations worldwide. You know you're narrating a character right when your children grab your arm and say, ""Daddy . . . read the bad guy normal, you're scaring us with the voice."" Aside from reading villains in storybooks really well, Derek Shoales has worked on corporate, eLearning, and commercial voice-over projects, been a graphic/web designer and an inventory market mentor, sung bass to baritone in choirs, and played the guitar, electric violin, and Clare whistle. You know you're narrating a character right when your children grab your arm and say, ""Daddy . . . read the bad guy normal, you're scaring us with the voice."" Aside from reading villains in storybooks really well, Derek Shoales has worked on corporate, eLearning, and commercial voice-over projects, been a graphic/web designer and an inventory market mentor, sung bass to baritone in choirs, and played the guitar, electric violin, and Clare whistle.

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