Item #:
142421830
The Hundred-Page Language Models Book: hands-on with PyTorch (The Hundred-Page Books)
85% of respondents would recommend this to a friend
Item #:
142421830
MMK 258891
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Master language models through mathematics, illustrations, and code—and build your own from scratch!
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What Stands Out
Concise Learning
This book provides a clear and concise introduction to language models, ensuring that readers grasp essential concepts quickly and efficiently for practical applications.
Hands-on Approach
Offering practical exercises with PyTorch, this book empowers readers to build and experiment with language models, enhancing retention and skill development through active engagement.
Up-to-Date Content
Published in 2025, the book includes the latest advancements in language modeling, equipping readers with the most current techniques and best practices in the field.
Product Details
- Master language models through mathematics, illustrations, and code―and build your own from scratch!The Hundred-Page Language Models Book by Andriy Burkov, the follow-up to his bestselling The Hundred-Page Machine Learning Book (now in 12 languages), offers a concise yet thorough journey from language modeling fundamentals to the cutting edge of modern Large Language Models (LLMs). Within Andriy's famous hundred-page format, readers will master both theoretical concepts and practical implementations, making it an invaluable resource for developers, data scientists, and machine learning engineers.The Hundred-Page Language Models Book allows you to:- Master the mathematical foundations of modern machine learning and neural networks- Build and train three architectures of language models in Python- Understand and code a Transformer language model from scratch in PyTorch- Work with LLMs, including instruction finetuning and prompt engineeringWritten in a hands-on style with working Python code examples, this book progressively builds your understanding from basic machine learning concepts to advanced language model architectures. All code examples run on Google Colab, making it accessible to anyone with a modern laptop.About the technologyLanguage models have evolved from simple n-gram statistics to become one of the most transformative technologies in AI, rivaling only personal computers in their impact. This book spans the complete evolution—from count-based methods to modern Transformer architectures—delivering a thorough understanding of both how these models work and how to implement them.About the bookThe Hundred-Page Language Models Book takes a unique approach by introducing language modeling concepts gradually, starting with foundational methods before advancing to modern architectures. Each chapter builds upon the previous one, making complex concepts accessible through clear explanations, diagrams, and practical implementations.What's inside- Essential machine learning and neural network fundamentals- Text representation techniques and basic language modeling- Implementation of RNNs and Transformer architectures with PyTorch- Practical guidance on finetuning language models and prompt engineering- Important considerations on hallucinations and ways to evaluate models- Additional resources for advanced topics through the book's wikiThe complete code and additional resources are available through the book's website at thelmbook.com/wiki.About the readerReaders should have programming experience in Python. While familiarity with PyTorch and tensors is helpful, it's not required. College-level math knowledge is beneficial, but the book presents mathematical concepts intuitively with clear examples and diagrams.Endorsements from tech and AI leadersVint Cerf, Internet pioneer and Turing Award recipient: This book cleared up a lot of conceptual confusion for me about how Machine Learning actually works - it is a gem of clarity.Tomáš Mikolov, the author of word2vec and FastText: The book is a good start for anyone new to language modeling who aspires to improve on state of the art.Florian Douetteau, co-founder and CEO at Dataiku: Andriy paints for us, in 100 marvelous strokes, the journey from linear algebra basics to the implementation of transformers.Jerry Liu, co-founder and CEO at LlamaIndex: This is one of the most comprehensive yet concise handbooks out there for truly understanding how LLMs work under the hood.More endorsements from AI leaders on thelmbook.com.
| Publisher | True Positive Inc. |
| Publication date | 15 Jan. 2025 |
| Language | English |
| Print length | 156 pages |
| ISBN-10 | 1778042724 |
| ISBN-13 | 978-1778042720 |
| Dimensions | 19.05 x 0.94 x 23.5 cm |
| Part of series | The Hundred-Page Books |
Who Should Buy?
-
Aspiring Data Scientists
Provides practical insights and hands-on experience with language models and PyTorch for those starting their careers.
-
Machine Learning Enthusiasts
Offers valuable resources and learning materials for individuals passionate about advancing their knowledge in language models.
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Students in AI
Serves as an excellent supplementary textbook for students pursuing courses in artificial intelligence and machine learning.
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Complete Beginners
Assumes prior knowledge of programming and machine learning concepts, making it challenging for absolute beginners.
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English edition Andriy Burkov Format: Paperback Editorial Review
The Hundred-Page Language Models Book: Hands-on With PyTorch offers an insightful dive into the world of language models. With 156 pages published by True Positive Inc., this book stands out for its ability to convert complex ideas into understandable concepts, making it an ideal resource for both beginners and those with some experience in AI/ML/DL. Readers appreciate the intuitive illustrations and structured approach, which provides a comprehensive understanding of topics ranging from neural networks to advanced Transformer architectures. Highly recommended by enthusiasts, this book not only covers theory but also emphasizes practical application, ensuring readers leave with valuable insights.
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Pros
- Great for beginners and experienced readers
- Clear and intuitive illustrations
- Well-structured and educational content
- Practical applications alongside theory
- Engaging writing style makes it enjoyable
Cons
- Some readers might prefer more in-depth coverage
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MMK 258891
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Features & Benefits
- Concise yet thorough exploration of language modeling fundamentals.
- Build and train three architectures of language models in Python.
- Understand and code a Transformer language model from scratch using PyTorch.
- Accessible coding examples to enhance practical implementation skills.
- Progressive learning approach, making complex concepts clear and understandable.
- Suitable for developers, data scientists, and machine learning engineers.
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