£124.84

Morgan Kaufmann - Probability for Deep Learning Quantum Book

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Description

Explore advanced mathematical concepts with Probability for Deep Learning Quantum: A Many-Sorted Algebra View. Published by Morgan Kaufmann, this technical text provides a specialized perspective on the intersection of probability, deep learning, and quantum mechanics through the lens of many-sorted algebra. This book serves as a resource for those studying computer science, artificial intelligence, and machine learning. By focusing on a many-sorted algebra view, it offers a structured way to approach complex probabilistic models used in modern computing. Whether you are researching AI foundations or quantum computing applications, this title provides the necessary theoretical framework for your academic or professional studies. Designed for the academic community and technical professionals, this publication from Morgan Kaufmann fits into the essential library for anyone pursuing deep learning and quantum-related research. It addresses the mathematical requirements needed to understand the evolving landscape of machine learning and computational theory.

Key Features

Technical deep dive into many-sorted algebra as applied to probability and quantum mechanics.

Specialized content designed for the fields of deep learning and artificial intelligence.

Published by Morgan Kaufmann, a recognized name in professional and academic computing literature.

Provides a formal mathematical framework for understanding complex machine learning models.

Targeted at researchers and students in computer science and advanced computational studies.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
31 January 2025
Listed Since
22 May 2024

Barcode

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