{ "item_title" : "Mathematical Foundations and Transformer Principles", "item_author" : [" Wei Sun "], "item_description" : "The Transformer Principles Series is a three-volume graduate-level treatise that builds a complete mathematical and engineering understanding of modern AI systems, from the foundational attention mechanism to large language models and multimodal architectures. Volume I - Mathematical Foundations and Transformer Principles begins with the historical evolution from symbolic AI to deep learning, then develops the essential mathematics: linear algebra, probability, optimization, neural network backpropagation, and information theory. These tools are applied through a systematic construction of the Transformer - self-attention, multi-head projections, positional encodings, feed-forward networks, residual connections, and normalization - culminating in the complete encoder-decoder architecture and an exploration of efficient attention variants, mixture-of-experts, and state-space models.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/9/79/818/209/9798182096218_b.jpg", "price_data" : { "retail_price" : "79.99", "online_price" : "79.99", "our_price" : "79.99", "club_price" : "79.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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