
Transformer, BERT, and GPT
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This book offers an in-depth exploration of the Transformer architecture, BERT models, and the GPT series, including GPT-3 and GPT-4. Beginning with foundational concepts like the attention mechanism and tokenization techniques, it delves into the intricacies of Transformer and BERT architectures. Advanced topics cover the latest developments in the GPT series, including ChatGPT. Key chapters provide insights into the evolution and significance of attention in deep learning, the nuances of Transformer architecture, a detailed exploration of the BERT family, and hands-on guidance on working with GPT-3. The journey continues with a comprehensive overview of ChatGPT, GPT-4, and visualization using generative AI. The book also discusses influential AI organizations such as DeepMind, OpenAI, Cohere, and Hugging Face. Readers will gain a thorough understanding of the current landscape of NLP models, their underlying architectures, and practical applications. Companion files with numerous code samples and figures from the book enhance the learning experience, providing practical tools and resources. This book is an essential guide for those seeking to master the latest advancements in natural language processing and generative AI.
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File format: ePUB
Copy protection: without DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Use a reader that can handle the file format ePUB, such as Adobe Digital Editions or FBReader – both free (see eBook Help).
- Tablet/Smartphone (Android; iOS): Install the free app Adobe Digital Editions or the app PocketBook (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (not Kindle).
The file format ePUB works well for novels and non-fiction books – i.e., 'flowing' text without complex layout. On an e-reader or smartphone, line and page breaks automatically adjust to fit the small displays.
This eBook does not use copy protection or Digital Rights Management
For more information, see our eBook Help page.