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Key benefits

Learn how to build Python-driven solutions with a focus on NLP, LLMs, RAGs, and GPT

Master embedding techniques and machine learning principles for real-world applications

Understand the mathematical foundations of NLP and deep learning designs

Purchase of the print or Kindle book includes a free PDF eBook

Description

Do you want to master Natural Language Processing (NLP) but don’t know where to begin? This book will give you the right head start. Written by leaders in machine learning and NLP, Mastering NLP from Foundations to LLMs provides an in-depth introduction to techniques. Starting with the mathematical foundations of machine learning (ML), you’ll gradually progress to advanced NLP applications such as large language models (LLMs) and AI applications. You’ll get to grips with linear algebra, optimization, probability, and statistics, which are essential for understanding and implementing machine learning and NLP algorithms. You’ll also explore general machine learning techniques and find out how they relate to NLP. Next, you’ll learn how to preprocess text data, explore methods for cleaning and preparing text for analysis, and understand how to do text classification. You’ll get all of this and more along with complete Python code samples. By the end of the book, the advanced topics of LLMs’ theory, design, and applications will be discussed along with the future trends in NLP, which will feature expert opinions. You’ll also get to strengthen your practical skills by working on sample real-world NLP business problems and solutions.

Who is this book for?

This book is for deep learning and machine learning researchers, NLP practitioners, ML/NLP educators, and STEM students. Professionals working with text data as part of their projects will also find plenty of useful information in this book. Beginner-level familiarity with machine learning and a basic working knowledge of Python will help you get the best out of this book.

What you will learn

Master the mathematical foundations of machine learning and NLP Implement advanced techniques for preprocessing text data and analysis Design ML-NLP systems in Python

Model and classify text using traditional machine learning and deep learning methods

Understand the theory and design of LLMs and their implementation for various applications in AI

Explore NLP insights, trends, and expert opinions on its future direction and potential

What do you get with Print?

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Colour book shipped to your preferred address

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

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Frequently bought together

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Amazon verified reviews

Fon Marile May 23, 2024

Mastering NLP is an invaluable resource for anyone in the NLP field. It provides a thorough grounding in essential math and programming, along with advanced techniques for text classification and LLM system design. With practical python examples and expert insights, its a must-read for NLP mastery and when seeking a reliable guide when tackling real world problems.

Amazon Verified review

Petar Dimov Jun 21, 2024

🎉 This comprehensive guide has proved itself to be an invaluable resource!💡 The book captivated me from the first chapter itself. It brilliantly paves the way for everyone from budding learners to industry veterans in the space of NLP and LLMs, and its concise yet comprehensive coverage aligns perfectly with the needs of a wide array of readers.🧠 Gazit and Ghaffari have meticulously crafted this book as a powerful compendium of knowledge. They have intelligently structured the content to segue from fundamental understanding of topics like linear algebra, probability, and statistics to more advanced ML techniques, making it an essential manual of NLP-related learnings.✏️ What sets this book apart is not merely the actionable insight it provides, but how it beautifully combines these insights with real-life applications. The transition from text pre-processing techniques to deep learning models, discussed from Chapter 4 through 6, is skillfully supplemented with Python-based case studies, creating a truly immersive learning experience.🛠 For those fascinated by Large Language Models (LLMs), Chapters 7 to 9 delve into everything from theory and design to sophisticated applications like prompt engineering and RAGs, all of which are brought to life through practical code implementations.🧩 The final chapters (10 and 11) critically analyse the current trends influenced by AI and LLMs, while also making well-researched predictions about the future of this industry, preparing readers to stay ahead of the curve.✨ In summary, "Mastering NLP from Foundations to LLMs" is more than just a book; it is a well-rounded guide for anyone keen to tap into the potential of NLP and LLMs. This guide offers an impressive mix of foundational theories, actionable insights, and future forecasts, all while ensuring reader-friendly delivery. Whether you're a beginner or a professional, this book is a brilliant tool to navigate the complex yet exciting world of AI and LLMs.

Andrew May 26, 2024

As a business leader this is a good source for me to refer to. It simplifies complex NLP concepts and also provides practical Python examples to just run and play with.This book empowers leaders by letting better understand what actually happens which feeds into strategic decision-making and driving innovation.Ideally, this would help be competitive in an AI-driven market.

yifat May 29, 2024

This NLP book is a powerful resource for job candidates. It directly prepares you for Machine Learning Engineer interviews by covering essential system design concepts, advanced NLP techniques, and practical Python examples.You get the insight you need, so it's worth keeping at your desk.

Sarbjit Singh Hanjra Oct 18, 2024

"Mastering NLP from Foundations to LLMs", serves as that crucial guide, helping readers chart their course through the expansive field of Natural Language Processing (NLP).From the basics of NLP and machine learning to advanced topics like neural networks, transformers, and LLMs, this book lays out the landscape clearly. It begins by grounding readers in essential mathematical concepts, including linear algebra and probability, before guiding them through data exploration and machine learning models. The book’s strength lies in its structured approach, making even the most complex topics—like text preprocessing, hyperparameter tuning, and ensemble models—easy to digest.The sections dedicated to LLMs are like detailed flight maps for advanced NLP techniques. From designing and integrating LLMs with LangChain and RAG to practical applications using Hugging Face, the book ensures you're well-equipped to navigate these models effectively. Highly recommended for those looking to master NLP, this guide is the perfect roadmap to understanding and leveraging the power of LLMs.

Mastering NLP from Foundations to LLMs: Apply advanced rule-based techniques to LLMs and solve real-world business problems using Python

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