The Mathematical Methods of Artificial Intelligence Purpose, Role, and Real-World Application Beneath every chatbot, recommendation engine, and image classifier lies not a single mysterious algorithm — but a small, precise set of mathematical methods, each doing a specific job. This book names them, explains them, and shows exactly where they work inside systems you use every day. "The mystery, on inspection, resolves into a toolkit — and this book is a guide to the tools." Twelve chapters, one method each. Linear algebra encodes a Netflix film as a vector of hidden tastes. Calculus finds the direction of improvement inside a training loop. Gradient descent walks that direction, step by step, until a language model learns to predict language as people actually write it. Probability turns uncertain evidence into a Gmail spam decision. Information theory supplies the very measure of error that trains ChatGPT. And logic — the oldest method of all — still guarantees, with mathematical certainty, that aircraft software will never fail in a way no test ever caught. Every chapter follows the same structure: definition · purpose · role in AI · key formulas · one real system. Read in sequence, the chapters build from foundation upward. Read singly, each stands as a self-contained reference. No advanced background is assumed beyond basic algebra and a willingness to read an equation as a compact sentence. Inside this book: Linear algebra → Netflix recommendations · Calculus → Image classifier training · Gradient descent → GPT-family LLMs · Probability → Gmail spam filter · Statistics → A/B testing at scale · Information theory → ChatGPT word prediction · Regression → Credit scoring (FICO) · Distance & similarity → Spotify playlists · Neural networks → Voice assistants (Siri) · Dimensionality reduction → Eigenfaces & face ID · Graph theory → Google PageRank · Logic & symbols → Formal verification.
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Paperback. Zustand: new. Paperback. The Mathematical Methods of Artificial Intelligence Purpose, Role, and Real-World Application Beneath every chatbot, recommendation engine, and image classifier lies not a single mysterious algorithm - but a small, precise set of mathematical methods, each doing a specific job. This book names them, explains them, and shows exactly where they work inside systems you use every day. "The mystery, on inspection, resolves into a toolkit - and this book is a guide to the tools." Twelve chapters, one method each. Linear algebra encodes a Netflix film as a vector of hidden tastes. Calculus finds the direction of improvement inside a training loop. Gradient descent walks that direction, step by step, until a language model learns to predict language as people actually write it. Probability turns uncertain evidence into a Gmail spam decision. Information theory supplies the very measure of error that trains ChatGPT. And logic - the oldest method of all - still guarantees, with mathematical certainty, that aircraft software will never fail in a way no test ever caught. Every chapter follows the same structure: definition - purpose - role in AI - key formulas - one real system. Read in sequence, the chapters build from foundation upward. Read singly, each stands as a self-contained reference. No advanced background is assumed beyond basic algebra and a willingness to read an equation as a compact sentence. Inside this book: Linear algebra Netflix recommendations - Calculus Image classifier training - Gradient descent GPT-family LLMs - Probability Gmail spam filter - Statistics A/B testing at scale - Information theory ChatGPT word prediction - Regression Credit scoring (FICO) - Distance & similarity Spotify playlists - Neural networks Voice assistants (Siri) - Dimensionality reduction Eigenfaces & face ID - Graph theory Google PageRank - Logic & symbols Formal verification. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9789999345422
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Paperback. Zustand: new. Paperback. The Mathematical Methods of Artificial Intelligence Purpose, Role, and Real-World Application Beneath every chatbot, recommendation engine, and image classifier lies not a single mysterious algorithm - but a small, precise set of mathematical methods, each doing a specific job. This book names them, explains them, and shows exactly where they work inside systems you use every day. "The mystery, on inspection, resolves into a toolkit - and this book is a guide to the tools." Twelve chapters, one method each. Linear algebra encodes a Netflix film as a vector of hidden tastes. Calculus finds the direction of improvement inside a training loop. Gradient descent walks that direction, step by step, until a language model learns to predict language as people actually write it. Probability turns uncertain evidence into a Gmail spam decision. Information theory supplies the very measure of error that trains ChatGPT. And logic - the oldest method of all - still guarantees, with mathematical certainty, that aircraft software will never fail in a way no test ever caught. Every chapter follows the same structure: definition - purpose - role in AI - key formulas - one real system. Read in sequence, the chapters build from foundation upward. Read singly, each stands as a self-contained reference. No advanced background is assumed beyond basic algebra and a willingness to read an equation as a compact sentence. Inside this book: Linear algebra Netflix recommendations - Calculus Image classifier training - Gradient descent GPT-family LLMs - Probability Gmail spam filter - Statistics A/B testing at scale - Information theory ChatGPT word prediction - Regression Credit scoring (FICO) - Distance & similarity Spotify playlists - Neural networks Voice assistants (Siri) - Dimensionality reduction Eigenfaces & face ID - Graph theory Google PageRank - Logic & symbols Formal verification. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Bestandsnummer des Verkäufers 9789999345422
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Paperback. Zustand: new. Paperback. The Mathematical Methods of Artificial Intelligence Purpose, Role, and Real-World Application Beneath every chatbot, recommendation engine, and image classifier lies not a single mysterious algorithm - but a small, precise set of mathematical methods, each doing a specific job. This book names them, explains them, and shows exactly where they work inside systems you use every day. "The mystery, on inspection, resolves into a toolkit - and this book is a guide to the tools." Twelve chapters, one method each. Linear algebra encodes a Netflix film as a vector of hidden tastes. Calculus finds the direction of improvement inside a training loop. Gradient descent walks that direction, step by step, until a language model learns to predict language as people actually write it. Probability turns uncertain evidence into a Gmail spam decision. Information theory supplies the very measure of error that trains ChatGPT. And logic - the oldest method of all - still guarantees, with mathematical certainty, that aircraft software will never fail in a way no test ever caught. Every chapter follows the same structure: definition - purpose - role in AI - key formulas - one real system. Read in sequence, the chapters build from foundation upward. Read singly, each stands as a self-contained reference. No advanced background is assumed beyond basic algebra and a willingness to read an equation as a compact sentence. Inside this book: Linear algebra Netflix recommendations - Calculus Image classifier training - Gradient descent GPT-family LLMs - Probability Gmail spam filter - Statistics A/B testing at scale - Information theory ChatGPT word prediction - Regression Credit scoring (FICO) - Distance & similarity Spotify playlists - Neural networks Voice assistants (Siri) - Dimensionality reduction Eigenfaces & face ID - Graph theory Google PageRank - Logic & symbols Formal verification. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9789999345422
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The Mathematical Methods of Artificial Intelligence Purpose, Role, and Real-World Application Beneath every chatbot, recommendation engine, and image classifier lies not a single mysterious algorithm - but a small, precise set of mathematical methods, each doing a specific job. This book names them, explains them, and shows exactly where they work inside systems you use every day. 'The mystery, on inspection, resolves into a toolkit - and this book is a guide to the tools.' Twelve chapters, one method each. Linear algebra encodes a Netflix film as a vector of hidden tastes. Calculus finds the direction of improvement inside a training loop. Gradient descent walks that direction, step by step, until a language model learns to predict language as people actually write it. Probability turns uncertain evidence into a Gmail spam decision. Information theory supplies the very measure of error that trains ChatGPT. And logic - the oldest method of all - still guarantees, with mathematical certainty, that aircraft software will never fail in a way no test ever caught. Every chapter follows the same structure: definition purpose role in AI key formulas one real system. Read in sequence, the chapters build from foundation upward. Read singly, each stands as a self-contained reference. No advanced background is assumed beyond basic algebra and a willingness to read an equation as a compact sentence. Inside this book: Linear algebra ¿ Netflix recommendations Calculus ¿ Image classifier training Gradient descent ¿ GPT-family LLMs Probability ¿ Gmail spam filter Statistics ¿ A/B testing at scale Information theory ¿ ChatGPT word prediction Regression ¿ Credit scoring (FICO) Distance & similarity ¿ Spotify playlists Neural networks ¿ Voice assistants (Siri) Dimensionality reduction ¿ Eigenfaces & face ID Graph theory ¿ Google PageRank Logic & symbols ¿ Formal verification. Bestandsnummer des Verkäufers 9789999345422
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Taschenbuch. Zustand: Neu. The Mathematical Methods of Artificial Intelligence | Purpose, Role, and Real-World Application | Hafidha Sebbagh | Taschenbuch | Englisch | Eliva Press | EAN 9789999345422 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 136371011
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