Ahmed gad (205 resultados)

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Paperback or Softback. Condición: New. Rebellion in the Poetry of Allen Ginsberg (1926 - 1997): An M. A. Thesis submitted to: The Department of English Faculty of Arts Assiut University. Book.

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Paperback. Condición: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

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Condición: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.…

Condición: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.…

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New. Brand New, Softcover edition. This item may ship from the US or our Overseas warehouse depending on your location and stock availability.

Condición: New. Brand New, Softcover edition. This item may ship from the US or our Overseas warehouse depending on your location and stock availability.

Condición: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.…

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Condición: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books.

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Paperback. Condición: New. This book is a hands-on guide to understanding the foundations, architectures, and real-world applications of transformers and large language models in modern AI.The book begins by laying the foundations of generative AI architectures,  tokenization, encoding, and classical modeling techniques. Initial chapters address the evolution from feed-forward networks and recurrent neural networks to long short-term memory (LSTM), setting the stage for the revolutionary transformer architecture. The core of the book focuses on transformers, introducing the encoder-decoder framework, attention mechanisms, positional encodings, and the internal workings of multi-head attention, normalization, and multi-layer perceptrons. Readers gain insight into advanced techniques such as rotary positional embeddings (RoPE), mixture of experts (MoE), and knowledge distillation, alongside practical training strategies like self-supervised learning, fine-tuning, and reinforcement learning with human feedback. Popular models from OpenAI, DeepSeek, and other vendors are examined to highlight the evolution of the LLM landscape. Building on these foundations, the text explores methods for model customization, including parameter-efficient fine-tuning (LoRA, adapters), text generation strategies, prompt engineering, and quantization. Retrieval-Augmented Generation (RAG) is introduced as a critical innovation for grounding LLMs in external knowledge, with detailed evaluation techniques for retrieval and generation. Finally, the book ventures into Agentic AI, demonstrating protocols like Model Context Protocol (MCP) and Agent-to-Agent (A2A) interactions with practical coding examples.In conclusion, this book serves as both a practical guide, equipping readers with the technical depth and applied strategies needed to design, fine-tune, and deploy cutting-edge transformers and large language models for real-world applications.What we will learn:Ø  Understand the foundations of AI, ML pipelines, tokenization, encoding, and early neural architectures.Ø  Explore transformers in depth-encoder-decoder design, attention mechanisms, and advanced embedding methods.Ø  Learn modern LLM advancements like RoPE, MoE, SLMs, fine-tuning strategies, and evaluation techniques.Ø  Master practical customization through prompt engineering, PEFT methods, quantization, and text generation.nWho this book is for:Data scientists, ML engineers, AI researchers, and developers exploring Transformers and large language models.…

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paperback. Condición: New.

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Condición: New. Print on Demand.

Paperback. Condición: New. This book is a hands-on guide to understanding the foundations, architectures, and real-world applications of transformers and large language models in modern AI.The book begins by laying the foundations of generative AI architectures,  tokenization, encoding, and classical modeling techniques. Initial chapters address the evolution from feed-forward networks and recurrent neural networks to long short-term memory (LSTM), setting the stage for the revolutionary transformer architecture. The core of the book focuses on transformers, introducing the encoder-decoder framework, attention mechanisms, positional encodings, and the internal workings of multi-head attention, normalization, and multi-layer perceptrons. Readers gain insight into advanced techniques such as rotary positional embeddings (RoPE), mixture of experts (MoE), and knowledge distillation, alongside practical training strategies like self-supervised learning, fine-tuning, and reinforcement learning with human feedback. Popular models from OpenAI, DeepSeek, and other vendors are examined to highlight the evolution of the LLM landscape. Building on these foundations, the text explores methods for model customization, including parameter-efficient fine-tuning (LoRA, adapters), text generation strategies, prompt engineering, and quantization. Retrieval-Augmented Generation (RAG) is introduced as a critical innovation for grounding LLMs in external knowledge, with detailed evaluation techniques for retrieval and generation. Finally, the book ventures into Agentic AI, demonstrating protocols like Model Context Protocol (MCP) and Agent-to-Agent (A2A) interactions with practical coding examples.In conclusion, this book serves as both a practical guide, equipping readers with the technical depth and applied strategies needed to design, fine-tune, and deploy cutting-edge transformers and large language models for real-world applications.What we will learn:Ø  Understand the foundations of AI, ML pipelines, tokenization, encoding, and early neural architectures.Ø  Explore transformers in depth-encoder-decoder design, attention mechanisms, and advanced embedding methods.Ø  Learn modern LLM advancements like RoPE, MoE, SLMs, fine-tuning strategies, and evaluation techniques.Ø  Master practical customization through prompt engineering, PEFT methods, quantization, and text generation.nWho this book is for:Data scientists, ML engineers, AI researchers, and developers exploring Transformers and large language models.…