CUDA by Example

2010-07-19
CUDA by Example

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  • Author: Jason Sanders
  • Publisher: Addison-Wesley Professional
  • ISBN: 0132180138
  • Category : Computers
  • Languages : en
  • Pages : 524

CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required—just the ability to program in a modestly extended version of C. CUDA by Example, written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology. The authors introduce each area of CUDA development through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You’ll discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance. Major topics covered include Parallel programming Thread cooperation Constant memory and events Texture memory Graphics interoperability Atomics Streams CUDA C on multiple GPUs Advanced atomics Additional CUDA resources All the CUDA software tools you’ll need are freely available for download from NVIDIA. http://developer.nvidia.com/object/cuda-by-example.html

Think Bayes

2021-05-18
Think Bayes

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  • Author: Allen B. Downey
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1492089435
  • Category : Computers
  • Languages : en
  • Pages : 338

If you know how to program, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical formulas, using discrete probability distributions rather than continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer and you'll begin to apply these techniques to real-world problems. Bayesian statistical methods are becoming more common and more important, but there aren't many resources available to help beginners. Based on undergraduate classes taught by author Allen B. Downey, this book's computational approach helps you get a solid start. Use your programming skills to learn and understand Bayesian statistics Work with problems involving estimation, prediction, decision analysis, evidence, and Bayesian hypothesis testing Get started with simple examples, using coins, dice, and a bowl of cookies Learn computational methods for solving real-world problems

Fluent Python

2015-07-30
Fluent Python

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  • Author: Luciano Ramalho
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1491946253
  • Category : Computers
  • Languages : en
  • Pages : 755

Python’s simplicity lets you become productive quickly, but this often means you aren’t using everything it has to offer. With this hands-on guide, you’ll learn how to write effective, idiomatic Python code by leveraging its best—and possibly most neglected—features. Author Luciano Ramalho takes you through Python’s core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time. Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3. This book covers: Python data model: understand how special methods are the key to the consistent behavior of objects Data structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode age Functions as objects: view Python functions as first-class objects, and understand how this affects popular design patterns Object-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritance Control flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packages Metaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work

Interactive Data Visualization with Python

2020-04-14
Interactive Data Visualization with Python

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  • Author: Abha Belorkar
  • Publisher: Packt Publishing Ltd
  • ISBN: 1800201060
  • Category : Computers
  • Languages : en
  • Pages : 362

Create your own clear and impactful interactive data visualizations with the powerful data visualization libraries of Python Key FeaturesStudy and use Python interactive libraries, such as Bokeh and PlotlyExplore different visualization principles and understand when to use which oneCreate interactive data visualizations with real-world dataBook Description With so much data being continuously generated, developers, who can present data as impactful and interesting visualizations, are always in demand. Interactive Data Visualization with Python sharpens your data exploration skills, tells you everything there is to know about interactive data visualization in Python. You'll begin by learning how to draw various plots with Matplotlib and Seaborn, the non-interactive data visualization libraries. You'll study different types of visualizations, compare them, and find out how to select a particular type of visualization to suit your requirements. After you get a hang of the various non-interactive visualization libraries, you'll learn the principles of intuitive and persuasive data visualization, and use Bokeh and Plotly to transform your visuals into strong stories. You'll also gain insight into how interactive data and model visualization can optimize the performance of a regression model. By the end of the course, you'll have a new skill set that'll make you the go-to person for transforming data visualizations into engaging and interesting stories. What you will learnExplore and apply different interactive data visualization techniquesManipulate plotting parameters and styles to create appealing plotsCustomize data visualization for different audiencesDesign data visualizations using interactive librariesUse Matplotlib, Seaborn, Altair and Bokeh for drawing appealing plotsCustomize data visualization for different scenariosWho this book is for This book intends to provide a solid training ground for Python developers, data analysts and data scientists to enable them to present critical data insights in a way that best captures the user's attention and imagination. It serves as a simple step-by-step guide that demonstrates the different types and components of visualization, the principles, and techniques of effective interactivity, as well as common pitfalls to avoid when creating interactive data visualizations. Students should have an intermediate level of competency in writing Python code, as well as some familiarity with using libraries such as pandas.

Learning Spark

2015-01-28
Learning Spark

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  • Author: Holden Karau
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1449359051
  • Category : Computers
  • Languages : en
  • Pages : 289

Data in all domains is getting bigger. How can you work with it efficiently? Recently updated for Spark 1.3, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala. This edition includes new information on Spark SQL, Spark Streaming, setup, and Maven coordinates. Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. You’ll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning. Quickly dive into Spark capabilities such as distributed datasets, in-memory caching, and the interactive shell Leverage Spark’s powerful built-in libraries, including Spark SQL, Spark Streaming, and MLlib Use one programming paradigm instead of mixing and matching tools like Hive, Hadoop, Mahout, and Storm Learn how to deploy interactive, batch, and streaming applications Connect to data sources including HDFS, Hive, JSON, and S3 Master advanced topics like data partitioning and shared variables

Python Programming with Oracle Database

2009-08-01
Python Programming with Oracle Database

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  • Author: Ray Terrill
  • Publisher:
  • ISBN: 9781608300136
  • Category : Database management
  • Languages : en
  • Pages : 176

Ray Terrill's Python Programming for Oracle Database is a detailed exploration of the ways in which the Python programming language can be used to interact with the Oracle Relational Database Management System (RDBMS). As evidenced by the table of contents, the book covers the broad spectrum of Python/Oracle interactions, including standard SQL, PL/SQL, connecting as a SYSDBA user, and object-oriented database interactions. The book also takes time to provide primer sections for both the Python programming language and the Oracle Database, in the hopes of facilitating an easier learning experience for beginners to either discipline. This book provides information and examples not available in any other Python book. The examples are detailed enough to provide a solid understanding of the topics they're meant to reinforce, while being explained in thorough detail to ensure comprehension of key concepts. There is little doubt that the book will quickly pay for itself, as the reader stands to add valuable skills to their technical arsenal through the material covered throughout in each of the chapters. Topics covered in the book: Installation of Python/Required Software Modules; Python Introduction; Oracle Introduction; Using SQL with Python to Interact with Oracle; Performing DBA Tasks with the Oracle Database Using Python; Using PL/SQL with Python; Using an Object-Relational Mapper to Connect Python and Oracle.

Industry 4.1

2021-10-26
Industry 4.1

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  • Author: Fan-Tien Cheng
  • Publisher: John Wiley & Sons
  • ISBN: 1119739896
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 562

Industry 4.1 Intelligent Manufacturing with Zero Defects Discover the future of manufacturing with this comprehensive introduction to Industry 4.0 technologies from a celebrated expert in the field Industry 4.1: Intelligent Manufacturing with Zero Defects delivers an in-depth exploration of the functions of intelligent manufacturing and its applications and implementations through the Intelligent Factory Automation (iFA) System Platform. The book’s distinguished editor offers readers a broad range of resources that educate and enlighten on topics as diverse as the Internet of Things, edge computing, cloud computing, and cyber-physical systems. You’ll learn about three different advanced prediction technologies: Automatic Virtual Metrology (AVM), Intelligent Yield Management (IYM), and Intelligent Predictive Maintenance (IPM). Different use cases in a variety of manufacturing industries are covered, including both high-tech and traditional areas. In addition to providing a broad view of intelligent manufacturing and covering fundamental technologies like sensors, communication standards, and container technologies, the book offers access to experimental data through the IEEE DataPort. Finally, it shows readers how to build an intelligent manufacturing platform called an Advanced Manufacturing Cloud of Things (AMCoT). Readers will also learn from: An introduction to the evolution of automation and development strategy of intelligent manufacturing A comprehensive discussion of foundational concepts in sensors, communication standards, and container technologies An exploration of the applications of the Internet of Things, edge computing, and cloud computing The Intelligent Factory Automation (iFA) System Platform and its applications and implementations A variety of use cases of intelligent manufacturing, from industries like flat-panel, semiconductor, solar cell, automotive, aerospace, chemical, and blow molding machine Perfect for researchers, engineers, scientists, professionals, and students who are interested in the ongoing evolution of Industry 4.0 and beyond, Industry 4.1: Intelligent Manufacturing with Zero Defects will also win a place in the library of laypersons interested in intelligent manufacturing applications and concepts. Completely unique, this book shows readers how Industry 4.0 technologies can be applied to achieve the goal of Zero Defects for all product

z/TPF Application Modernization using Standard and Open Middleware

2013-06-28
z/TPF Application Modernization using Standard and Open Middleware

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  • Author: Lisa Dianne Banks
  • Publisher: IBM Redbooks
  • ISBN: 0738438200
  • Category : Computers
  • Languages : en
  • Pages : 486

In a world where product lifespans are often measured in months, the IBM® Transaction Processing Facility has remained relevant for more than four decades by continuing to process high volumes of transactions quickly and reliably. As the title of this book suggests, the z/TPF system uses open, standard interfaces to create services. Integration of new applications with existing z/TPF functions is a key factor in extending application capabilities. The ability for service data objects (SDO) to access the z/TPF Database Facility (z/TPFDF) provides a framework for data application program development that includes an architecture and application programming interfaces (APIs). SDO access to z/TPFDF provides remote client applications with access to z/TPF traditional data. In the simplest terms, service-oriented architecture (SOA) is a means by which like, or unlike, systems can communicate with one another despite differences between each system's heritage. SOA can neutralize the differences between systems so that they understand one another. SOA support for z/TPF is a means by which z/TPF can interact with other systems that also support SOA. This book discusses various aspects of SOA in the z/TPF system, including explanations and examples to help z/TPF users implement SOA. IBM WebSphere® Application Server was chosen as the partner system as a means of demonstrating how a world class transaction server and a world class application server can work together. This book shows you how you can exploit z/TPF as a transaction server, participating in a SOA structure alongside WebSphere Application Server. This IBM Redbooks® publication provides an introduction to z/TPF and the technologies critical to SOA. z/TPF is positioned as a provider or consumer in an SOA by supporting SOAP processing, communication bindings, and Extensible Markup Language (XML). An example is used to show how z/TPF can be used both as a Web service provider and as a consumer. A second example shows how to use WebSphere Operational Decision Management to apply business rules. A third example shows how business event processing can be incorporated in z/TPF applications. An example is also used to discuss security aspects, including z/TPF XML encryption and the z/TPF WS-Security wrapper. The main part of the book concludes with a discussion of z/TPF in an open systems environment, including examples of lightweight implementations to fit z/TPF, such as the HTTP server for the z/TPF system. The appendixes include information and examples using TPF Toolkit, sample code, and workarounds (with yes, more examples).

Machine Learning in Chemistry

2020-07-15
Machine Learning in Chemistry

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  • Author: Hugh M. Cartwright
  • Publisher: Royal Society of Chemistry
  • ISBN: 1788017897
  • Category : Science
  • Languages : en
  • Pages : 564

Progress in the application of machine learning (ML) to the physical and life sciences has been rapid. A decade ago, the method was mainly of interest to those in computer science departments, but more recently ML tools have been developed that show significant potential across wide areas of science. There is a growing consensus that ML software, and related areas of artificial intelligence, may, in due course, become as fundamental to scientific research as computers themselves. Yet a perception remains that ML is obscure or esoteric, that only computer scientists can really understand it, and that few meaningful applications in scientific research exist. This book challenges that view. With contributions from leading research groups, it presents in-depth examples to illustrate how ML can be applied to real chemical problems. Through these examples, the reader can both gain a feel for what ML can and cannot (so far) achieve, and also identify characteristics that might make a problem in physical science amenable to a ML approach. This text is a valuable resource for scientists who are intrigued by the power of machine learning and want to learn more about how it can be applied in their own field.

Learning Scrapy

2016-01-29
Learning Scrapy

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  • Author: Dimitris Kouzis - Loukas
  • Publisher:
  • ISBN: 9781784399788
  • Category : Computers
  • Languages : en
  • Pages : 270

Learn the art of efficient web scraping and crawling with PythonAbout This Book• Extract data from any source to perform real time analytics.• Full of techniques and examples to help you crawl websites and extract data within hours.• A hands-on guide to web scraping and crawling with real-life problems and solutionsWho This Book Is ForIf you are a software developer, data scientist, NLP or machine-learning enthusiast or just need to migrate your company's wiki from a legacy platform, then this book is for you. It is perfect for someone , who needs instant access to large amounts of semi-structured data effortlessly.What You Will Learn• Understand HTML pages and write XPath to extract the data you need• Write Scrapy spiders with simple Python and do web crawls• Push your data into any database, search engine or analytics system• Configure your spider to download files, images and use proxies• Create efficient pipelines that shape data in precisely the form you want• Use Twisted Asynchronous API to process hundreds of items concurrently• Make your crawler super-fast by learning how to tune Scrapy's performance• Perform large scale distributed crawls with scrapyd and scrapinghubIn DetailThis book covers the long awaited Scrapy v 1.0 that empowers you to extract useful data from virtually any source with very little effort. It starts off by explaining the fundamentals of Scrapy framework, followed by a thorough description of how to extract data from any source, clean it up, shape it as per your requirement using Python and 3rd party APIs. Next you will be familiarised with the process of storing the scrapped data in databases as well as search engines and performing real time analytics on them with Spark Streaming. By the end of this book, you will perfect the art of scarping data for your applications with easeStyle and approachIt is a hands on guide, with first few chapters written as a tutorial, aiming to motivate you and get you started quickly. As the book progresses, more advanced features are explained with real world examples that can be reffered while developing your own web applications.