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Titlebook: Introduction to Python and Large Language Models; A Guide to Language Dilyan Grigorov Book 2024 Dilyan Grigorov 2024 Computer Science.Info

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發(fā)表于 2025-3-21 18:02:55 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Introduction to Python and Large Language Models
副標(biāo)題A Guide to Language
編輯Dilyan Grigorov
視頻videohttp://file.papertrans.cn/477/476483/476483.mp4
概述Provides practical applications of LLMs, with essential NLP concepts such as text preprocessing, and sentiment analysis.Covers Python programming concepts such as Python syntax, data types, functions,
圖書(shū)封面Titlebook: Introduction to Python and Large Language Models; A Guide to Language Dilyan Grigorov Book 2024 Dilyan Grigorov 2024 Computer Science.Info
描述.Gain a solid foundation for Natural Language Processing (NLP) and Large Language Models (LLMs), emphasizing their significance in today’s computational world. This book is an introductory guide to NLP and LLMs with Python programming...The book starts with the basics of NLP and LLMs. It covers essential NLP concepts, such as text preprocessing, feature engineering, and sentiment analysis using Python. The book offers insights into Python programming, covering syntax, data types, conditionals, loops, functions, and object-oriented programming. Next, it delves deeper into LLMs, unraveling their complex components...You’ll learn about LLM elements, including embedding layers, feedforward layers, recurrent layers, and attention mechanisms. You’ll also explore important topics like tokens, token distributions, zero-shot learning, LLM hallucinations, and insights into popular LLM architectures such as GPT-4, BERT, T5, PALM, and others. Additionally, it covers Python libraries like Hugging Face, OpenAI API, and Cohere. The final chapter bridges theory with practical application, offering step-by-step examples of coded applications for tasks like text generation, summarization, language t
出版日期Book 2024
關(guān)鍵詞Computer Science; Informatics; Conference Proceedings; Research; Applications
版次1
doihttps://doi.org/10.1007/979-8-8688-0540-0
isbn_softcover979-8-8688-0539-4
isbn_ebook979-8-8688-0540-0
copyrightDilyan Grigorov 2024
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發(fā)表于 2025-3-21 22:45:56 | 只看該作者
What Are Large Language Models?,ir lives. However, machines lack an inherent ability to comprehend and communicate in human language unless equipped with powerful AI algorithms. The long-standing research challenge and aspiration have been to enable machines to attain human-like reading, writing, and communication skills.
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Basic Overview of the Components of the LLM Architectures,r appreciating how LLMs transform raw textual data into meaningful, context-aware outputs. The key components discussed in this chapter include .. Each of these plays a pivotal role in enabling LLMs to process and generate human-like language.
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Harnessing Python 3.11 and Python Libraries for LLM Development,from natural language processing to sophisticated AI-driven solutions. The advent of Python 3.11 brings a host of new features and optimizations that significantly enhance the development of these complex models. Coupled with an array of robust Python libraries, this chapter delves into the practica
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Hugging Face, OpenAI API, and Cohere. The final chapter bridges theory with practical application, offering step-by-step examples of coded applications for tasks like text generation, summarization, language t979-8-8688-0539-4979-8-8688-0540-0
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