An Introduction to MATLAB® Programming and Numerical Methods for Engineers


An Introduction to MATLAB® Programming and Numerical Methods for Engineers
By 作者:Timmy Siauw and Alexandre Bayen
pages 页数: 338 pages
Publisher Finelybook 出版社: Academic Press (18 April 2014)
Language 语言: English
ISBN-10 书号:0124202284
ISBN-13 书号:9780124202283
Book Description to Finelybook sorting
Assuming no prior background in linear algebra or real analysis, An Introduction to MATLAB® Programming and Numerical Methods for Engineers enables you to develop good computational problem solving techniques through the use of numerical methods and the MATLAB® programming environment. Part One introduces fundamental programming concepts, using simple examples to put new concepts quickly into practice. Part Two covers the fundamentals of algorithms and numerical analysis at a level allowing you to quickly apply results in practical settings.


An Introduction to MATLAB® Programming and Numerical Methods for Engineers 9780124202283.pdf

Coding for Beginners


Coding for Beginners: A step-By 作者:-step guide to thinking in Code and Coding yuour thinking
By 作者: Roger Engelbert
Pub Date: 2020
ISBN: 9781-912084-27-2
Pages 页数: 510
Language 语言: English
Format: EPUB/AZW3
Print pages 页数: 433 pages
Page Numbers Source ISBN: 1912084287
Sold By 作者:: Amazon Media EU S.à r.l.
Language 语言: English
ASIN: B08BX851C7
Book Description to Finelybook sorting
A step-By 作者:-step guide to programming using code done in Python, JavaScript, C#, and F#. With easy to follow examples, each new chapter building upon the knowledge and experience acquired in the previous ones. If you ever wanted to learn to program and thought the topic too complex or the books available on the topic too inscrutable, this is the guide for you.


Coding for Beginners

Implementing Cisco HyperFlex Solutions


Implementing Cisco HyperFlex Solutions (Networking Technology) 1st Edition
By 作者:Jalpa Patel (Author), Manuel Velasco (Author), Avinash Shukla (Author)
Series: Networking Technology
pages 页数: 400 pages
Publisher Finelybook 出版社: Cisco Press; 1 edition (July 16, 2020)
Language 语言: English
ISBN-10 书号:013660191X
ISBN-13 书号:9780136601913
Book Description to Finelybook sorting
Cisco’s HyperFlex HCI solutions enable exceptional datacenter efficiency, agility, and resiliency By 作者:tightly integrating core infrastructure (compute, storage, networking, and system management), increasing automation, and simplifying lifecycle management. In this authoritative and comprehensive guide, Cisco experts bring together all the knowledge, detailed configuration options, and real-world case studies you need to successfully deploy Cisco HyperFlex technologies in your environment.
This guide’s key features include:

Concise, easy-to-understand overviews of underlying concepts and how each HyperFlex technology applies them
Detailed reference examples for implementing each key feature, with topologies, configurations, and verifications
Thorough Intersight coverage to illuminate operations in cloud-based environments
Do’s and don’ts for successful, high-efficiency HyperFlex design
Best practice recommendations, guidelines, and caveats for avoiding pitfalls, streamlining deployment, and maximizing value


at a Glance
Chapter 1 Overview of Data Center Products
Chapter 2 HyperFlex Architecture
Chapter 3 Installing HyperFlex
Chapter 4 Managing HyperFlex
Chapter 5 Maintaining HyperFlex
Chapter 6 Advanced Features
Chapter 7 Deploying HyperFlex Anywhere with Cisco Intersight

Implementing Cisco HyperFlex Solutions

Management in the Era of Big Data: Issues and Challenges


Management in the Era of Big Data: Issues and Challenges (Data Analytics Applications)
By 作者:Joanna Paliszkiewicz
pages 页数: 248 pages
Publisher Finelybook 出版社: Auerbach Publications; 1 edition (15 Jun. 2020)
Language 语言: English
ISBN-10 书号:0367895579
ISBN-13 书号:9780367895570
Book Description to Finelybook sorting
Big Data is a concept that has caught the attention of practitioners, academicians, and researchers. Big Data offers organizations the possibility of gaining a competitive advantage By 作者:managing, collecting, and analyzing massive amounts of data. As the promises and challenges posed By 作者:Big Data have increased over the past decade, significant issues have developed regarding how data can be used for improving management. Big Data can be understood as large amounts of data generated By 作者:the Internet and a variety of connected smart devices and sensors.
This book discusses the main challenges posed By 作者:Big Data in a manner relevant to both practitioners and scholars. It examines how companies can leverage Big Data analytics to act and optimize the business. This book brings together the theory and practice of management in the era of Big Data. It offers a look at the current state of Big Data, including a comprehensive overview of both research and practical applications.
By bringing together conceptual thinking and empirical research on the nature, meaning, and development of Big Data in management, this book unifies research on Big Data in management to stimulate new directions for academic investigation as well as practice.


Management in the Era of Big Data Issues and Challenges 9780367895570.pdf

Tackling TypeScript: Upgrading from JavaScript


tackling typescript upgrading javascriptTackling TypeScript: Upgrading from JavaScript
By 作者: Dr. Axel Rauschmayer
Pub Date: 2020
ISBN: n/a
Pages 页数: 210
Language 语言: English
Format: PDF/EPUB
Size: 10 Mb
Book Description to Finelybook sorting
This book consists of two parts:

Part 1 is a quick start for TypeScript that teaches you the essentials quickly.
Part 2 digs deeper into the language and covers many important topics in detail.
This book is not a reference, it is meant to complement the official TypeScript handbook.
Upddate 2020-06-14
4 new chapters:

The top types any and unknown
Type assertions (related to casting)
Type guards and assertion functions
Validating external data
Switched from `@ts-ignore` to `@ts-expect-error`


Tackling TypeScript Upgrading from

Handbook of Research on Big Data Clustering and Machine Learning


By 作者: Fausto Pedro Garcia Marquez
Pub Date: 2020
ISBN: 9781799801061
Pages 页数: 478
Language 语言: English
Format: PDF
Size: 19 Mb
Book Description to Finelybook sorting
As organizations continue to develop, there is an increasing need for technological methods that can keep up with the rising amount of data and information that is being generated. Machine learning is a tool that has become powerful due to its ability to analyze large amounts of data quickly. Machine learning is one of many technological advancements that is being implemented into a multitude of specialized fields. An extensive study on the execution of these advancements within professional industries is necessary.
The Handbook of Research on Big Data Clustering and Machine Learning is an essential reference source that synthesizes the analytic principles of clustering and machine learning to big data and provides an interface between the main disciplines of engineering/technology and the organizational, administrative, and planning abilities of management. Featuring research on topics such as project management, contextual data modeling, and business information systems, this book is ideally designed for engineers, economists, finance officers, marketers, decision makers, business professionals, industry practitioners, academicians, students, and researchers seeking coverage on the implementation of big data and machine learning within specific professional fields.


Handbook of Research on Big Data Clustering and Machine Learning 9781799801061.pdf

Big Data in Astronomy: Scientific Data Processing for Advanced Radio Telescopes


Big Data in Astronomy: Scientific Data Processing for Advanced Radio Telescopes
By 作者:Linghe Kong (Editor), Tian Huang (Editor), Yongxin Zhu (Editor),
pages 页数: 438 pages
Publisher Finelybook 出版社: Elsevier (26 Jun. 2020)
Language 语言: English
ISBN-10 书号:0128190841
ISBN-13 书号:9780128190845
Book Description to Finelybook sorting
Big Data in Radio Astronomy: Scientific Data Processing for Advanced Radio Telescopes provides the latest research developments in big data methods and techniques for radio astronomy. Providing examples from such projects as the Square Kilometer Array (SKA), the world’s largest radio telescope that generates over an ExaBy 作者:te of data every day, the book offers solutions for coping with the challenges and opportunities presented By 作者:the exponential growth of astronomical data. Presenting state-of-the-art results and research, this book is a timely reference for both practitioners and researchers working in radio astronomy, as well as students looking for a basic understanding of big data in astronomy.


Big Data in Astronomy 9780128190845.pdf

Graphs, Algorithms, and Optimization, 2nd Edition


Graphs, Algorithms, and Optimization, Second Edition (Discrete Mathematics and Its Applications)

Graphs, Algorithms, and Optimization, Second Edition (Discrete Mathematics and Its Applications)
By 作者: William Kocay - Donald L. Kreher
ISBN-10 书号: 1482251167
ISBN-13 书号: 9781482251166
Edition 版本: 2
Release Finelybook 出版日期: 2016-09-26
Pages 页数: 566
Book Description to Finelybook sorting

The second edition of this popular book presents the theory of graphs from an algorithmic viewpoint. The authors present the graph theory in a rigorous, but informal style and cover most of the main areas of graph theory. The ideas of surface topology are presented from an intuitive point of view. We have also included a discussion on linear programming that emphasizes problems in graph theory. The text is suitable for students in computer science or mathematics programs.


Chapter 1: Graphs And Their Complements
Chapter 2: Paths And Walks
Chapter 3: Subgraphs
Chapter 4: Some Special Classes Of Graphs
Chapter 5: Trees And Cycles
Chapter 6: The Structure Of Trees
Chapter 7: Connectivity
Chapter 8: Graphs And Symmetry
Chapter 9: Alternating Paths And Matchings
Chapter 10: Network Flows
Chapter 11: Hamilton Cycles
Chapter 12: Digraphs
Chapter 13: Graph Colorings
Chapter 14: Planar Graphs
Chapter 15: Graphs And Surfaces
Chapter 16: The Klein Bottle And The Double Torus
Chapter 17: Linear Programming
Chapter 18: The Primal-Dual Algorithm
Chapter 19: Discrete Linear Programming

CRC Graphs Algorithms and Optimization 2nd Edition 9781482251166.pdf

Introduction to Middleware: Web Services, Object Components, and Cloud Computing


Introduction to Middleware: Web Services, Object Components, and Cloud ComputingIntroduction to Middleware: Web Services, Object Components, and Cloud Computing
By 作者: Letha Hughes Etzkorn
ISBN-10 书号: 1498754074
ISBN-13 书号: 9781498754071
Edition 版本: 1
Release Finelybook 出版日期: 2017-06-08
Pages 页数: 688
Book Description to Finelybook sorting
"A stereotype of computer science textbooks is that they are dry, boring, and sometimes even intimidating. As a result, they turn students’ interests off from the subject matter instead of enticing them into it. This textbook is the opposite of such a stereotype. The author presents the subject matter in a refreshing story-telling style and aims to bring the Internet-generation of students closer to her stories."?
--Yingcai Xiao, The University of Akron
Introduction to Middleware: Web Services, Object Components, and Cloud Computing provides a comparison of different middleware technologies and the overarching middleware concepts they are based on. The various major paradigms of middleware are introduced and their pros and cons are discussed. This includes modern cloud interfaces, including the utility of Service Oriented Architectures. The text discusses pros and cons of RESTful vs. non-RESTful web services, and also compares these to older but still heavily used distributed object/component middleware. The text guides readers to select an appropriate middleware technology to use for any given task, and to learn new middleware technologies as they appear over time without being greatly overwhelmed by any new concept.
The book begins with an introduction to different distributed computing paradigms, and a review of the different kinds of architectures, architectural styles/patterns, and properties that various researchers have used in the past to examine distributed applications and determine the quality of distributed applications. Then it includes appropriate background material in networking and the web, security, and encoding necessary to understand detailed discussion in this area. The major middleware paradigms are compared, and a comparison methodology is developed. Readers will learn how to select a paradigm and technology for a particular task, after reading this text.
Detailed middleware technology review sections allow students or industry practitioners working to expand their knowledge to achieve practical skills based on real projects so as to become well-functional in that technology in industry. Major technologies examined include: RESTful web services (RESTful cloud interfaces such as OpenStack, AWS EC2 interface, CloudStack; AJAX, JAX-RS, ASP.NET MVC and ASP.NET Core), non-RESTful (SOAP and WSDL-based) web services (JAX-WS, Windows Communication Foundation), distributed objects/ components (Enterprise Java Beans, .NET Remoting, CORBA).
The book presents two projects that can be used to illustrate the practical use of middleware, and provides implementations of these projects over different technologies.
This versatile and class-tested textbook is suitable (depending on chapters selected) for undergraduate or first-year graduate courses on client server architectures, middleware, and cloud computing, web services, and web programming.


SECTION I The Different Paradigms
Chapter 1 Introduction
Chapter 2 Software Architectural Styles/Patterns for Middleware
SECTION II Enabling Technologies for Middleware
Chapter 3 Introduction to Internet Technologies
Chapter 4 Introduction to World Wide Web Technologies
Chapter 5 Security Basics
Chapter 6 Microsoft Technologies Basics
Chapter 7 Cloud Technologies Basics
SECTION III Middleware Using Distributed Object-Oriented Components
Chapter 8 Distributed Object-Oriented Components
SECTION IV Middleware Using Web Services
Chapter 9 Web Services Architectures
Chapter 10 Non-RESTful Web Services
Chapter 11 RESTful Web Services
SECTION V Middleware for the Cloud
Chapter 13 Introduction to the Cloud and Introduction to the OpenStack Cloud
Chapter 14 Introduction to Amazon Web Services and Introduction to the CloudStack Cloud
SECTION VI Message-Oriented Middleware
Chapter 15 Introduction to Message-Oriented Middleware
SECTION VII Comparison of Middlewares
Chapter 16 Introduction to Comparing Middlewares


Introduction to Middleware Web Services, Object Components, and Cloud Computing

End-to-End Data Science with SAS: A Hands-On Programming Guide


End-to-End Data Science with SAS: A Hands-On Programming Guide
By 作者:James Gearheart
Pub Date: 2020
ISBN: 9781642958041
Pages 页数: 484
Language 语言: English
Format: EPUB
Size: 14 Mb
Book Description to Finelybook sorting
Learn data science concepts with real-world examples in SAS!
End-to-End Data Science with SAS: A Hands-On Programming Guide provides clear and practical explanations of the data science environment, machine learning techniques, and the SAS programming knowledge necessary to develop machine learning models in any industry. The book covers concepts including understanding the business need, creating a modeling data set, linear regression, parametric classification models, and non-parametric classification models. Real-world business examples and example code are used to demonstrate each process step-By 作者:-step.
Although a significant amount of background information and supporting mathematics are presented, the book is not structured as a textbook, but rather it is a user’s guide for the application of data science and machine learning in a business environment. Readers will learn how to think like a data scientist, wrangle messy data, choose a model, and evaluate the model’s effectiveness. New data scientists or professionals who want more experience with SAS will find this book to be an invaluable reference. Take your data science career to the next level By 作者:mastering SAS programming for machine learning models.


End-to-End Data Science with SAS