Concise Metals Engineering Data Book

Concise Metals Engineering Data Book PDF Author: Joseph R. Davis
Publisher: ASM International
ISBN: 161503983X
Category : Technology & Engineering
Languages : en
Pages : 257

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Book Description

Concise Metals Engineering Data Book

Concise Metals Engineering Data Book PDF Author: Joseph R. Davis
Publisher: ASM International
ISBN: 161503983X
Category : Technology & Engineering
Languages : en
Pages : 257

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Book Description


Data-Driven Science and Engineering

Data-Driven Science and Engineering PDF Author: Steven L. Brunton
Publisher: Cambridge University Press
ISBN: 1009098489
Category : Computers
Languages : en
Pages : 615

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Book Description
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

ASME Engineer's Data Book

ASME Engineer's Data Book PDF Author: Clifford Matthews
Publisher: American Society of Mechanical Engineers
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 388

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Book Description
This greatly expanded second edition of this popular and handy reference book includes over 100 new pages, including extensive coverage of Section VIII of the ASME Pressure Vessel Code. Divided into 22 sections, this pocket-sized volume is an exhaustive "quick reference" of up-to-date engineering data and rules. It includes: essential mathematics; units; engineering design processes and principles; basic mechanical design; motion; mechanics of materials; material failure; thermodynamics; fluid mechanics; fluid equipment; vessel codes and standards; materials; machine elements; design and production tools; project engineering; computer-aided engineering; welding; non-destructive examination; corrosion; surface protection; metallurgical terms; and engineering associations and organizations.

Data Engineering with Google Cloud Platform

Data Engineering with Google Cloud Platform PDF Author: Adi Wijaya
Publisher: Packt Publishing Ltd
ISBN: 1800565062
Category : Computers
Languages : en
Pages : 440

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Book Description
Build and deploy your own data pipelines on GCP, make key architectural decisions, and gain the confidence to boost your career as a data engineer Key Features Understand data engineering concepts, the role of a data engineer, and the benefits of using GCP for building your solution Learn how to use the various GCP products to ingest, consume, and transform data and orchestrate pipelines Discover tips to prepare for and pass the Professional Data Engineer exam Book DescriptionWith this book, you'll understand how the highly scalable Google Cloud Platform (GCP) enables data engineers to create end-to-end data pipelines right from storing and processing data and workflow orchestration to presenting data through visualization dashboards. Starting with a quick overview of the fundamental concepts of data engineering, you'll learn the various responsibilities of a data engineer and how GCP plays a vital role in fulfilling those responsibilities. As you progress through the chapters, you'll be able to leverage GCP products to build a sample data warehouse using Cloud Storage and BigQuery and a data lake using Dataproc. The book gradually takes you through operations such as data ingestion, data cleansing, transformation, and integrating data with other sources. You'll learn how to design IAM for data governance, deploy ML pipelines with the Vertex AI, leverage pre-built GCP models as a service, and visualize data with Google Data Studio to build compelling reports. Finally, you'll find tips on how to boost your career as a data engineer, take the Professional Data Engineer certification exam, and get ready to become an expert in data engineering with GCP. By the end of this data engineering book, you'll have developed the skills to perform core data engineering tasks and build efficient ETL data pipelines with GCP.What you will learn Load data into BigQuery and materialize its output for downstream consumption Build data pipeline orchestration using Cloud Composer Develop Airflow jobs to orchestrate and automate a data warehouse Build a Hadoop data lake, create ephemeral clusters, and run jobs on the Dataproc cluster Leverage Pub/Sub for messaging and ingestion for event-driven systems Use Dataflow to perform ETL on streaming data Unlock the power of your data with Data Studio Calculate the GCP cost estimation for your end-to-end data solutions Who this book is for This book is for data engineers, data analysts, and anyone looking to design and manage data processing pipelines using GCP. You'll find this book useful if you are preparing to take Google's Professional Data Engineer exam. Beginner-level understanding of data science, the Python programming language, and Linux commands is necessary. A basic understanding of data processing and cloud computing, in general, will help you make the most out of this book.

Data Engineering on Azure

Data Engineering on Azure PDF Author: Vlad Riscutia
Publisher: Simon and Schuster
ISBN: 1617298921
Category : Computers
Languages : en
Pages : 334

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Book Description
Build a data platform to the industry-leading standards set by Microsoft’s own infrastructure. Summary In Data Engineering on Azure you will learn how to: Pick the right Azure services for different data scenarios Manage data inventory Implement production quality data modeling, analytics, and machine learning workloads Handle data governance Using DevOps to increase reliability Ingesting, storing, and distributing data Apply best practices for compliance and access control Data Engineering on Azure reveals the data management patterns and techniques that support Microsoft’s own massive data infrastructure. Author Vlad Riscutia, a data engineer at Microsoft, teaches you to bring an engineering rigor to your data platform and ensure that your data prototypes function just as well under the pressures of production. You'll implement common data modeling patterns, stand up cloud-native data platforms on Azure, and get to grips with DevOps for both analytics and machine learning. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Build secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify. About the book In Data Engineering on Azure you’ll learn the skills you need to build and maintain big data platforms in massive enterprises. This invaluable guide includes clear, practical guidance for setting up infrastructure, orchestration, workloads, and governance. As you go, you’ll set up efficient machine learning pipelines, and then master time-saving automation and DevOps solutions. The Azure-based examples are easy to reproduce on other cloud platforms. What's inside Data inventory and data governance Assure data quality, compliance, and distribution Build automated pipelines to increase reliability Ingest, store, and distribute data Production-quality data modeling, analytics, and machine learning About the reader For data engineers familiar with cloud computing and DevOps. About the author Vlad Riscutia is a software architect at Microsoft. Table of Contents 1 Introduction PART 1 INFRASTRUCTURE 2 Storage 3 DevOps 4 Orchestration PART 2 WORKLOADS 5 Processing 6 Analytics 7 Machine learning PART 3 GOVERNANCE 8 Metadata 9 Data quality 10 Compliance 11 Distributing data

Data-Driven Engineering Design

Data-Driven Engineering Design PDF Author: Ang Liu
Publisher: Springer Nature
ISBN: 3030881814
Category : Technology & Engineering
Languages : en
Pages : 203

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Book Description
This book addresses the emerging paradigm of data-driven engineering design. In the big-data era, data is becoming a strategic asset for global manufacturers. This book shows how the power of data can be leveraged to drive the engineering design process, in particular, the early-stage design. Based on novel combinations of standing design methodology and the emerging data science, the book presents a collection of theoretically sound and practically viable design frameworks, which are intended to address a variety of critical design activities including conceptual design, complexity management, smart customization, smart product design, product service integration, and so forth. In addition, it includes a number of detailed case studies to showcase the application of data-driven engineering design. The book concludes with a set of promising research questions that warrant further investigation. Given its scope, the book will appeal to a broad readership, including postgraduate students, researchers, lecturers, and practitioners in the field of engineering design.

Engineering Data on Mixing

Engineering Data on Mixing PDF Author: Reiji Reiji Mezaki
Publisher: Elsevier
ISBN: 0080531008
Category : Technology & Engineering
Languages : en
Pages : 781

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Book Description
This book is a compilation of the engineering data on mixing, which have appeared in the major technical journals of chemical engineering and bioengineering since 1975. That year marked the beginning of a period of rapid advancement in the science and technology of mixing, with rather reliable results for both theoretical and experimental studies. In addition, some important earlier articles which have been, and still are being referred to, are included.Designs of both agitators and tanks still depend primarily on art and experience. In light of this it was felt that the data on mixing should be compiled and presented in a systematic manner to assist in design and analysis of agitated tanks, and to provide easier access to mixing data for various engineering activities. Although computer-aided searches of pertinent data bases can be of assistance to chemical engineers and bioengineers in their studies, they are sometimes time-consuming and often costly. Furthermore inadequate selection of key words can jeopardize the searches. This book offers an alternative method of surveying mixing data which interests readers. The first chapter presents a variety of results for the experimental measurements of flow patterns in stirred tanks. Most of the measurements were made by using modern Laser-Doppler techniques. This chapter is useful for the prediction of flow patterns in tanks with many different geometries, various types of agitators, and fluids of diverse physical and rheological properties, plus valuable data for the validation of results obtained by CFD simulations. Chapters 2 through 5 deal with data for traditional chemical engineering subjects and Chapter 6 summarizes a number of scale-up relations developed over the years for various systems. These include liquid, solid-liquid, liquid-liquid, gas-liquid, and solid-liquid-gas systems. Chapter 7 provides data related to multiphase processes, and most importantly, drop size and drop-size distributions and bubble-size distributions. These two subjects have not been treated systematically either in text books or in handbooks on stirred-tank mixing, although the results of both experimental and theoretical investigations have been reported on many occasions. Finally gas-inducing mechanically agitated systems are dealt with. The applications of this type of agitation system will become increasingly attractive from the standpoint of rationalization of stirred-tank operations as well as environmental protection.

Data Network Engineering

Data Network Engineering PDF Author: Tim King
Publisher: Springer Science & Business Media
ISBN: 9780792385943
Category : Computers
Languages : en
Pages : 360

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Book Description
It is certain that, over the next few years, data traffic will dwarf voice traffic on telecommunications networks. Growth in data-traffic volumes far exceeds that for voice, and is driven by increased use of applications such as e-mail attachments, remote printing and fileserver access, and the now omnipresent World Wide Web. The growth of data networking to connect computers with each other and with their peripheral devices began in earnest in the 1970s, took off in the 1980s and exploded in the 1990s. The early 21st century will see ever faster, more cost effective networks providing flexible data access into ever more businesses and homes. Since the 1970s there have been great advances in technology. For the past twenty years the processing power of computers has continued to grow with no hint of slowing - recall the oft-cited Moore's Law claiming that this power doubles every 18 months. Advances in the data networking equipment required to support the data traffic generated have been enormous. The pace of development from early X. 25 and modem technology through to some of the advanced equipment functionality now available is breathtaking - it is sometimes hard to believe that the practical router is barely ten years old! This book provides an overview of the advanced data networking field by bringing together chapters on local area networks, wide area networks and their application.

The Rails Way

The Rails Way PDF Author: Obie Fernandez
Publisher: Pearson Education
ISBN: 032163019X
Category : Computers
Languages : en
Pages : 951

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Book Description
The expert guide to building Ruby on Rails applications Ruby on Rails strips complexity from the development process, enabling professional developers to focus on what matters most: delivering business value. Now, for the first time, there’s a comprehensive, authoritative guide to building production-quality software with Rails. Pioneering Rails developer Obie Fernandez and a team of experts illuminate the entire Rails API, along with the Ruby idioms, design approaches, libraries, and plug-ins that make Rails so valuable. Drawing on their unsurpassed experience, they address the real challenges development teams face, showing how to use Rails’ tools and best practices to maximize productivity and build polished applications users will enjoy. Using detailed code examples, Obie systematically covers Rails’ key capabilities and subsystems. He presents advanced programming techniques, introduces open source libraries that facilitate easy Rails adoption, and offers important insights into testing and production deployment. Dive deep into the Rails codebase together, discovering why Rails behaves as it does— and how to make it behave the way you want it to. This book will help you Increase your productivity as a web developer Realize the overall joy of programming with Ruby on Rails Learn what’s new in Rails 2.0 Drive design and protect long-term maintainability with TestUnit and RSpec Understand and manage complex program flow in Rails controllers Leverage Rails’ support for designing REST-compliant APIs Master sophisticated Rails routing concepts and techniques Examine and troubleshoot Rails routing Make the most of ActiveRecord object-relational mapping Utilize Ajax within your Rails applications Incorporate logins and authentication into your application Extend Rails with the best third-party plug-ins and write your own Integrate email services into your applications with ActionMailer Choose the right Rails production configurations Streamline deployment with Capistrano

Statistics and Data Analysis for Financial Engineering

Statistics and Data Analysis for Financial Engineering PDF Author: David Ruppert
Publisher: Springer
ISBN: 1493926144
Category : Business & Economics
Languages : en
Pages : 736

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Book Description
The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.