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Taschenbuch. Zustand: Neu. Neuware - Most machine learning books ask you to trust the black box. This one doesn't. From Zero to Agents rebuilds artificial intelligence from first principles - starting at the question of what a word even is to a computer, and ending with a working, tool-using AI agent you build yourself. Every concept is explained three ways: theoretically, mathematically, and in code - first written from scratch in raw Python, then reimplemented in PyTorch, so you always know exactly what the library is doing for you. This is not a tutorial that skips the hard parts. Every equation is derived. Every result is verified by running the code - including the places where the first attempt didn't work, and the book says so. Inside, you'll build: - Tokenization and embeddings, from raw text to trainable vectors- The mathematical toolkit - vectors, matrices, gradients, probability - explained through working code, not abstract proofs- A complete neural network, with backpropagation derived and verified by hand- Recurrent networks, LSTMs, and a full transformer with real multi-head attention, trained from scratch- LoRA fine-tuning, derived and measured, not just described- A working AI agent - tool use, memory, multi-agent coordination - arriving at the book's own titleWritten for practitioners who want to open a real AI/ML research paper and read the mathematics fluently, on sight - not skim past it to the prose.…

Paperback. Zustand: Brand New. 160 pages. 8.50x5.91x0.63 inches. In Stock.

Zustand: Like New. Used - Like New. Book is new and unread but may have minor shelf wear. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.…

Paperback. Zustand: new. Paperback. Most machine learning books ask you to trust the black box. This one doesn't. From Zero to Agents rebuilds artificial intelligence from first principles - starting at the question of what a word even is to a computer, and ending with a working, tool-using AI agent you build yourself. Every concept is explained three ways: theoretically, mathematically, and in code - first written from scratch in raw Python, then reimplemented in PyTorch, so you always know exactly what the library is doing for you. This is not a tutorial that skips the hard parts. Every equation is derived. Every result is verified by running the code - including the places where the first attempt didn't work, and the book says so. Inside, you'll build: Tokenization and embeddings, from raw text to trainable vectorsThe mathematical toolkit - vectors, matrices, gradients, probability - explained through working code, not abstract proofsA complete neural network, with backpropagation derived and verified by handRecurrent networks, LSTMs, and a full transformer with real multi-head attention, trained from scratchLoRA fine-tuning, derived and measured, not just describedA working AI agent - tool use, memory, multi-agent coordination - arriving at the book's own titleWritten for practitioners who want to open a real AI/ML research paper and read the mathematics fluently, on sight - not skim past it to the prose. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Zustand: New. Print on Demand.

PAP. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Zustand: new. Paperback. Most machine learning books ask you to trust the black box. This one doesn't. From Zero to Agents rebuilds artificial intelligence from first principles - starting at the question of what a word even is to a computer, and ending with a working, tool-using AI agent you build yourself. Every concept is explained three ways: theoretically, mathematically, and in code - first written from scratch in raw Python, then reimplemented in PyTorch, so you always know exactly what the library is doing for you. This is not a tutorial that skips the hard parts. Every equation is derived. Every result is verified by running the code - including the places where the first attempt didn't work, and the book says so. Inside, you'll build: Tokenization and embeddings, from raw text to trainable vectorsThe mathematical toolkit - vectors, matrices, gradients, probability - explained through working code, not abstract proofsA complete neural network, with backpropagation derived and verified by handRecurrent networks, LSTMs, and a full transformer with real multi-head attention, trained from scratchLoRA fine-tuning, derived and measured, not just describedA working AI agent - tool use, memory, multi-agent coordination - arriving at the book's own titleWritten for practitioners who want to open a real AI/ML research paper and read the mathematics fluently, on sight - not skim past it to the prose. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…