The Mathematical Methods of Artificial Intelligence: Purpose, Role, and Real-World Application

Name: The Mathematical Methods of Artificial Intelligence: Purpose, Role, and Real-World Application
Brand: Eliva Press
SKU: 9789999345422
Price: 3803.0 INR
Availability: InStock

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ISBN13: 9789999345422
Binding: Paperback
Subject: N/A
Publisher: Eliva Press
Publisher Imprint: Eliva Press
Publication Date: July 18, 1905
Pages: 68
Original Price: USD 49.5
Language: English
Edition: N/A
Item Weight: 105 grams
BISAC Subject(s): General

About The Book

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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