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Amazon Customer Oct 26, 2024

This book is a remarkable resource for anyone eager to dive into the world of Natural Language Processing (NLP). Authored by two seasoned NLP experts, this book offers a recipe-based approach that effectively addresses real-world text analysis challenges.One of the main strengths of this edition is its focus on the latest advancements in NLP, particularly large language models (LLMs) like GPT-4, and the practical application of these technologies using Hugging Face transformers. The authors provide a wealth of hands-on recipes that guide readers through essential techniques, such as entity extraction, sentiment analysis, and topic modeling, using popular libraries like spaCy, Gensim, and NLTK. This practical approach makes complex concepts accessible, allowing both beginners and seasoned developers to enhance their skills.The addition of new chapters on Natural Language Understanding (NLU) and Explainable AI (XAI) enriches the content, fostering a deeper understanding of model transparency and trustworthiness—an increasingly important aspect of AI applications. By the end of the book, readers will be well-equipped to build custom NLP pipelines and apply advanced techniques to extract valuable insights from text data.

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Om S Oct 15, 2024

The Python Natural Language Processing Cookbook offers a hands-on, recipe-based approach to mastering NLP techniques, making it a valuable resource for both beginners and experienced developers. This second edition stands out by introducing the latest in Large Language Models (LLMs), such as GPT-4, Mistral, and Llama, while covering foundational NLP concepts like text classification, topic modeling, and information extraction. With practical examples using popular tools like Hugging Face and OpenAI, the book excels in showcasing how to implement LLM-powered agents and advanced NLP tasks. The new chapters on transformers, explainable AI, and natural language understanding (NLU) make it particularly relevant for anyone eager to dive into cutting-edge NLP technologies. Whether you're just starting out or looking to enhance your expertise, this book provides clear, actionable insights into NLP's evolving landscape.

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Advitya Gemawat Oct 16, 2024

Throughout the book, I appreciated the infusion of both traditional NLP and GenAI concepts in almost every chapter of the book, which helps in ‘grounding’ GenAI concepts in foundational knowledge (get the pun? :))Here're my top takeaways from the book:📖 The traditional NLP content in Chapters 1 and 3-6 closely mirrors what I studied and utilized during college, making it a relevant resource for college students in similar NLP/AI classes.🏫 The dedicated Chapter 8 on Transformers is likely my top pick as a common topic for interview prep across multiple levels of recent grads and experienced AI practitioners.📊 Among all the content on LLMs, the 2 topics that especially stood out to me were the coding examples on:(1) Running an LLM locally, for quick experimentation and for college students with limited access to cloud resources(2) Building an Agent workflow: The ease of initializing built-in tools to perform actions like internet search as a reasoning step is honestly quite refreshing, due to the democratization of typical Function Calling capabilities that it demonstrates.More than anything, it's especially fun to get a refresher on foundational concepts and then position these in context of using modern tools that help build workflows at a higher level of abstraction.

Amazon Verified review

SA Sep 13, 2024

This book is a practical guide for solving NLP problems using Python. The book contains over 60 easy-to-follow recipes that help readers learn everything from basic NLP tasks like tokenization and lemmatization to more advanced topics, including transformers and large language models.The book is useful for a wide range of readers, from data scientists to software developers, because it explains concepts clearly and provides code examples that can be used right away. One of the highlights is that it covers the latest trends, like GPT models and transformers, which makes the book relevant in today’s fast-changing NLP field.Even though the book covers complex topics, it keeps the explanations simple, making it easy to understand and apply. The focus on Python and its libraries, like spaCy and Hugging Face, may limit its appeal for those looking for more general NLP approaches across different platforms.Overall, I found this book to be an excellent resource, motivating me to work on modern NLP projects with Python. It serves both as a learning guide and a useful reference for practical applications.

Amazon Verified review

Udbhav Nov 11, 2024

This book is an absolute must-have for anyone interested in diving into NLP, especially with a focus on large language models (LLMs) and transformers. As a data scientist, I've worked with NLP before, but I found this book incredibly helpful for bridging some of the latest advancements with practical implementation. The authors do a fantastic job breaking down complex concepts into easy-to-understand recipes, which you can directly apply to real-world challenges.Each chapter covers a specific NLP task, from the basics of text classification and sentiment analysis to more advanced techniques like RAG pipelines and Explainable AI (XAI). The section on Hugging Face and OpenAI models is especially valuable—it shows how to utilize the latest transformer models like GPT-4 and Llama. These are techniques I’ve been wanting to implement, and this book gave me the confidence and steps to start using them in my own projects.What sets this book apart is how approachable it is. You don’t need a background in NLP, just a solid grasp of Python. The recipe format is perfect if you’re short on time and want to get straight to the coding. Each recipe is concise but packed with insights, making it easy to go from understanding to implementing.For me, the real bonus was the focus on transparency in model predictions through XAI—it’s rare to find such a strong emphasis on building trust in AI models. Overall, a well-rounded book that has earned a permanent place on my desk. Highly recommend it to both beginners and experienced developers looking to expand their NLP skillset! Read more

Amazon Verified review

Python Natural Language Processing Cookbook: Over 60 recipes for building powerful NLP solutions using Python and LLM libraries , Second Edition

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