Edition internationale

Architecture of Advanced Numerical Analysis Systems

Liang Wang,Jianxin Zhao

ISBN 10: 1484288521 ISBN 13: 9781484288528
Edité par Apress, 2022
Neuf(s) Couverture souple

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Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide. N° de réf. du vendeur ABNR-209397

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Synopsis :

This unique open access book applies the functional OCaml programming language to numerical or computational weighted data science, engineering, and scientific applications. This book is based on the authors' first-hand experience building and maintaining Owl, an OCaml-based numerical computing library. 

You'll first learn the various components in a modern numerical computation library. Then, you will learn how these components are designed and built up and how to optimize their performance. After reading and using this book, you'll have the knowledge required to design and build real-world complex systems that effectively leverage the advantages of the OCaml functional programming language.

What You Will Learn

  • Optimize core operations based on N-dimensional arrays
  • Design and implement an industry-level algorithmic differentiation module
  • Implement mathematical optimization, regression, and deep neural network functionalities based on algorithmic differentiation
  • Design and optimize a computation graph module, and understand the benefits it brings to the numerical computing library
  • Accommodate the growing number of hardware accelerators (e.g. GPU, TPU) and execution backends (e.g. web browser, unikernel) of numerical computation
  • Use the Zoo system for efficient scripting, code sharing, service deployment, and composition
  • Design and implement a distributed computing engine to work with a numerical computing library, providing convenient APIs and high performance

Who This Book Is For
Those with prior programming experience, especially with the OCaml programming language, or with scientific computing experience who may be new to OCaml. Most importantly, it is for those who are eager to understand not only how to use something, but also how it is built up.

À propos de l?auteur:

Liang Wang is the Chief AI Architect at Nokia, the Chief Scientific Officer at iKVA, a Senior Researcher at the University of Cambridge, and an Intel Software Innovator. He has a broad research interest in artificial intelligence, machine learning, operating systems, computer networks, optimization theory, and graph theory.

Jianxin Zhao is a PhD graduate from the University of Cambridge, supervised by Prof. Jon Crowcroft. His research interests include numerical computation, high-performance computing, machine learning, and their application in the real world.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Détails bibliographiques

Titre : Architecture of Advanced Numerical Analysis ...
Éditeur : Apress
Date d'édition : 2022
Reliure : Couverture souple
Etat : New
Edition : Edition internationale

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Jianxin Zhao, Liang Wang
Edité par Apress, 2022
ISBN 10 : 1484288521 ISBN 13 : 9781484288528
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Etat : Sehr gut. Zustand: Sehr gut | Seiten: 488 | Sprache: Englisch | Produktart: Bücher | This unique open access book applies the functional OCaml programming language to numerical or computational weighted data science, engineering, and scientific applications. This book is based on the authors' first-hand experience building and maintaining Owl, an OCaml-based numerical computing library. You'll first learn the various components in a modern numerical computation library. Then, you will learn how these components are designed and built up and how to optimize their performance. After reading and using this book, you'll have the knowledge required to design and build real-world complex systems that effectively leverage the advantages of the OCaml functional programming language. What You Will LearnOptimize core operations based on N-dimensional arraysDesign and implement an industry-level algorithmic differentiation moduleImplement mathematical optimization, regression, and deep neural network functionalities based on algorithmic differentiationDesign and optimize a computation graph module, and understand the benefits it brings to the numerical computing libraryAccommodate the growing number of hardware accelerators (e.g. GPU, TPU) and execution backends (e.g. web browser, unikernel) of numerical computationUse the Zoo system for efficient scripting, code sharing, service deployment, and compositionDesign and implement a distributed computing engine to work with a numerical computing library, providing convenient APIs and high performance Who This Book Is For Those with prior programming experience, especially with the OCaml programming language, or with scientific computing experience who may be new to OCaml. Most importantly, it is for those who are eager to understand not only how to use something, but also how it is built up. N° de réf. du vendeur 40308195/2

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Jianxin Zhao, Liang Wang
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Etat : Hervorragend. Zustand: Hervorragend | Seiten: 488 | Sprache: Englisch | Produktart: Bücher | This unique open access book applies the functional OCaml programming language to numerical or computational weighted data science, engineering, and scientific applications. This book is based on the authors' first-hand experience building and maintaining Owl, an OCaml-based numerical computing library. You'll first learn the various components in a modern numerical computation library. Then, you will learn how these components are designed and built up and how to optimize their performance. After reading and using this book, you'll have the knowledge required to design and build real-world complex systems that effectively leverage the advantages of the OCaml functional programming language. What You Will LearnOptimize core operations based on N-dimensional arraysDesign and implement an industry-level algorithmic differentiation moduleImplement mathematical optimization, regression, and deep neural network functionalities based on algorithmic differentiationDesign and optimize a computation graph module, and understand the benefits it brings to the numerical computing libraryAccommodate the growing number of hardware accelerators (e.g. GPU, TPU) and execution backends (e.g. web browser, unikernel) of numerical computationUse the Zoo system for efficient scripting, code sharing, service deployment, and compositionDesign and implement a distributed computing engine to work with a numerical computing library, providing convenient APIs and high performance Who This Book Is For Those with prior programming experience, especially with the OCaml programming language, or with scientific computing experience who may be new to OCaml. Most importantly, it is for those who are eager to understand not only how to use something, but also how it is built up. N° de réf. du vendeur 40308195/1

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Paperback. Etat : New. This unique open access book applies the functional OCaml programming language to numerical or computational weighted data science, engineering, and scientific applications. This book is based on the authors' first-hand experience building and maintaining Owl, an OCaml-based numerical computing library. You'll first learn the various components in a modern numerical computation library. Then, you will learn how these components are designed and built up and how to optimize their performance. After reading and using this book, you'll have the knowledge required to design and build real-world complex systems that effectively leverage the advantages of the OCaml functional programming language. What You Will LearnOptimize core operations based on N-dimensional arraysDesign and implement an industry-level algorithmic differentiation moduleImplement mathematical optimization, regression, and deep neural network functionalities based on algorithmic differentiationDesign and optimize a computation graph module, and understand the benefits it brings to the numerical computing libraryAccommodate the growing number of hardware accelerators (e.g. GPU, TPU) and execution backends (e.g. web browser, unikernel) of numerical computationUse the Zoo system for efficient scripting, code sharing, service deployment, and compositionDesign and implement a distributed computing engine to work with a numerical computing library, providing convenient APIs and high performance Who This Book Is For Those with prior programming experience, especially with the OCaml programming language, or with scientific computing experience who may be new to OCaml. Most importantly, it is for those who are eager to understand not only how to use something, but also how it is built up. N° de réf. du vendeur LU-9781484288528

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