Python Natural Language Processing Cookbook: Over 60 recipes for building powerful NLP solutions using Python and LLM libraries
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Python Natural Language Processing Cookbook: Over 60 recipes for building powerful NLP solutions using Python and LLM libraries
Harness the power of Natural Language Processing (NLP) to overcome real-world text analysis challenges with this recipe-based roadmap.
Python Natural Language Processing Cookbook: Over 60 recipes for building powerful NLP solutions using Python and LLM libraries
Numéro d'article: 102690263

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

86% des répondants recommanderaient ceci à un ami

Numéro d'article: 102690263

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Harness the power of Natural Language Processing (NLP) to overcome real-world text analysis challenges with this recipe-based roadmap.
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Ce qui se démarque

Comprehensive Recipes
Features over 60 detailed recipes, guiding users through various NLP tasks. This extensive coverage ensures that readers can find practical solutions to diverse challenges in natural language processing.
Updated Libraries
Incorporates the latest advancements in Python and LLM libraries, ensuring that users leverage the most effective tools available for building robust NLP applications in the evolving tech landscape.
Hands-on Approach
Adopts a hands-on methodology that encourages experimentation. Readers can quickly apply techniques, allowing for real-world NLP projects to enhance learning and skill development in Python.

Détails du produit

Shop Python Natural Language Processing Cookbook: Over 60 recipes for building powerful NLP solutions using Python and LLM libraries online at a best price in Switzerland. 1803245743
  • Updated to include three new chapters on transformers, natural language understanding (NLU) with explainable AI, and dabbling with popular LLMs from Hugging Face and OpenAIKey FeaturesLeverage ready-to-use recipes with the latest LLMs, including Mistral, Llama, and OpenAI modelsUse LLM-powered agents for custom tasks and real-world interactionsGain practical, in-depth knowledge of transformers and their role in implementing various NLP tasks with open-source and advanced LLMsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionHarness the power of Natural Language Processing (NLP) to overcome real-world text analysis challenges with this recipe-based roadmap written by two seasoned NLP experts with vast experience transforming various industries with their NLP prowess.You’ll be able to make the most of the latest NLP advancements, including large language models (LLMs), and leverage their capabilities through Hugging Face transformers. Through a series of hands-on recipes, you’ll master essential techniques such as extracting entities and visualizing text data. The authors will expertly guide you through building pipelines for sentiment analysis, topic modeling, and question-answering using popular libraries like spaCy, Gensim, and NLTK. You’ll also learn to implement RAG pipelines to draw out precise answers from a text corpus using LLMs.This second edition expands your skillset with new chapters on cutting-edge LLMs like GPT-4, Natural Language Understanding (NLU), and Explainable AI (XAI)—fostering trust in your NLP models.By the end of this book, you'll be equipped with the skills to apply advanced text processing techniques, use pre-trained transformer models, build custom NLP pipelines to extract valuable insights from text data to drive informed decision-making.What you will learnUnderstand fundamental NLP concepts along with their applications using examples in PythonClassify text quickly and accurately with rule-based and supervised methodsTrain NER models and perform sentiment analysis to identify entities and emotions in textExplore topic modeling and text visualization to reveal themes and relationships within textLeverage Hugging Face and OpenAI LLMs to perform advanced NLP tasksUse question-answering techniques to handle both open and closed domainsApply XAI techniques to better understand your model predictionsWho this book is forThis updated edition of the Python Natural Language Processing Cookbook is for data scientists, machine learning engineers, and developers with a background in Python. Whether you’re looking to learn NLP techniques, extract valuable insights from textual data, or create foundational applications, this book will equip you with basic to intermediate skills. No prior NLP knowledge is necessary to get started. All you need is familiarity with basic programming principles. For seasoned developers, the updated sections offer the latest on transformers, explainable AI, and Generative AI with LLMs.Table of ContentsLearning NLP BasicsPlaying with GrammarRepresenting Text – Capturing SemanticsClassifying TextsGetting Started with Information ExtractionTopic ModelingVisualizing Text DataTransformers and Their ApplicationsNatural Language UnderstandingGenerative AI and Large Language Models
Publisher Packt Publishing
Publication date September 13, 2024
Edition 2nd ed.
Language English
Print length 312 pages
ISBN-10 1803245743
ISBN-13 978-1803245744
Item Weight 1.19 pounds (540 grams)
Dimensions 7.5 x 0.71 x 9.25 inches (19.1 x 1.8 x 23.5 cm)

À qui est-ce destiné ?

Suitable For
  • NLP Practitioners

    Ideal for NLP developers seeking practical recipes to implement solutions using Python and large language models.

  • Data Scientists

    Great for data scientists looking to incorporate NLP techniques into their projects to extract insights from textual data.

  • Students and Learners

    Beneficial for students aiming to learn NLP concepts through hands-on recipes tailored for different skill levels.

Not Suitable For
  • Absolute Beginners

    Not suitable for those with no programming experience, as it requires foundational knowledge of Python and NLP.

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Intelligence & Semantics Editorial Review

The "Python Natural Language Processing Cookbook: Over 60 Recipes for Building Powerful NLP Solutions Using Python and LLM Libraries" (2nd Edition) by Zhenya Antić, PhD and Saurabh Chakravarty is receiving widespread acclaim for its user-friendly, recipe-based approach to exploring and mastering natural language processing (NLP). This book stands out for both beginners and seasoned practitioners in the field, providing over 60 hands-on recipes that address a diverse array of NLP tasks. Reviewers appreciate the authors’ ability to simplify complex concepts, breaking down sophisticated topics such as transformers, large language models (LLMs), and Explainable AI (XAI) into digestible sections. This accessibility is particularly beneficial for readers who are new to NLP but have a solid foundation in Python. Each recipe not only covers the theoretical requirements but also guides the reader through practical implementations, demonstrating their use in real-world scenarios. The book excels in its focus on the latest advancements in the field, including how to effectively utilize models like GPT-4 and Llama. Reviewers have noted the depth and breadth of topics covered, ranging from basic text classification and sentiment analysis to more advanced techniques like RAG pipelines and building chatbots. The inclusion of case studies and real-life applications enhances the learning experience, making it both engaging and relevant. Moreover, many readers specifically point to the emphasis on transparency in AI predictions through XAI as a unique aspect of the book, reinforcing the importance of trust in AI models. This feature sets the book apart from others in the market that may overlook this critical component in their teaching. Overall, this cookbook is heralded as an essential resource for anyone eager to harness the power of NLP through Python. Its structured layout, practical focus, and approachable writing style make it a highly recommended choice for developers looking to deepen their knowledge and skills in NLP. **

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Avantages

  • Comprehensive coverage of both basic and advanced NLP topics.
  • User-friendly, with a recipe-based format that is easy to follow.
  • Excellent for both beginners and experienced practitioners.
  • Focus on the latest advancements in NLP and practical applications of LLMs like GPT-4.
  • Strong emphasis on Explainable AI for building trust in models.
  • Real-world examples and hands-on recipes enhance engagement and learning.

Les inconvénients

  • May require prior knowledge of Python programming for optimal understanding.

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Caractéristiques et avantages

  • Learn practical NLP techniques with hands-on recipes.
  • Master the use of the latest LLMs like GPT-4 and OpenAI models.
  • Build custom NLP pipelines for tasks like sentiment analysis and topic modeling.
  • Gain insights from integrating Hugging Face transformers into projects.
  • Perfect for data scientists, machine learning engineers, and Python developers.
  • Includes a free PDF eBook with the purchase of the print or Kindle version.

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