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Learn from Scratch Large Language Model (Full Colour Edition)
Paperback
Publisher Price: $49.99
ISBN13: 9789355427267
Publisher: Shroff/X-Team
Published: Mar 6 2025
Pages: 258
Weight: 1.23
Height: 0.70 Width: 7.00 Depth: 9.19
Language: English
In this comprehensive and accessible resource, you'll embark on an exciting journey that begins with the fundamentals of Natural Language Processing and progresses to advanced topics like instruction Fine-tuning and task-specific optimisation. With hands-on examples, practical exercises, and detailed explanations, this book equips you with the tools and knowledge needed to master LLMs from the ground up.
Foundations of LLMs: Learn the principles behind language modelling, tokenization, and Pretraining. Explore how models like GPT-2, GPT-3, and their successors understand and generate human-like text.
Building Blocks of Al: Understand the architecture of transformer-based models, the role of attention mechanisms, and how these innovations revolutionised the field of NLP.
Instruction Fine-tuning: Dive into the cutting-edge technique of instruction Fine-tuning. Learn how to teach LLMs to follow diverse prompts for tasks like creative writing, programming, and customer support.
Hands-On Applications: Use real-world datasets to fine-tune models for grammar correction,summarisation and context-aware conversations. Discover how LLMs are reshaping industries like education, healthcare, and e-commerce.
Automated Evaluation and Scalability: Leverage advanced evaluation methods, including the integration of larger models like Llama 3, to assess and optimize your fine-tuned models.
Practical Insights and Tips: Benefit from best practices for dataset preparation, hyper-parameter tuning, and avoiding common pitfalls during training.
Packed with illustrative examples and code snippets, Learn from Scratch: Large Language Models makes complex concepts accessible to learners at all levels. Whether you're starting your Al journey or expanding your expertise, this book provides the knowledge and confidence to create and customize LLMs for a wide range of applications.
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