AI has acquired startling new language capabilities in just the past few years. Driven by the rapid advances in Deep Learning, language AI systems are able to write and understand text better than ever before. This trend enables the rise of new features, products, and entire industries. With this book, Python developers will learn the practical tools and concepts they need to use these capabilities today. You’ll learn how to use the power of pre-trained large language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; build systems that classify and cluster text to enable scalable understanding of large amounts of text documents; and use existing libraries and pre-trained models for text classification, search, and clusterings. Large language models (LLMs) have had a profound and far-reaching impact on the world. By enabling machines to better understand and generate human-like language, LLMs have opened new possibilities in the field of AI and impacted entire industries. This book provides a comprehensive and highly visual introduction to the world of LLMs, covering both the conceptual foundations and practical applications. This book assumes that you have some experience programming in Python and are familiar with the fundamentals of Machine Learning. The focus will be on building a strong intuition rather than deriving mathematical equations. As such, illustrations combined with hands-on examples will drive the examples and learning through this book. This book assumes no prior knowledge of popular Deep Learning frameworks such as PyTorch or TensorFlow nor any prior knowledge of generative modeling.

Hands-On Large Language Models: Language Understanding and Generation PDF

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