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Are you ready to execute a cloud computing plan? You need a strategy to prepare for the future, and this book comes to the rescue. Authors Daniel Kirsch and Judith Hurwitz share insights by honing in on topics like multicloud architecture, microservices, hybrid infrastructure, DevOps, and Software as a Service. This book is ideal for anyone who needs to understand the emerging approaches to cloud computing.
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"Machine learning with big data technologies create new opportunities to understand the various data process related to medical or environmental aspects of agriculture. Machine learning as a field is now incredibly pervasive, with applications spanning from business intelligence to homeland security from analyzing biochemical interactions to structural monitoring of aging bridges, and from emissions to astrophysics, etc. As we are entering the Industrial Revolution 4.0, BD/ML applications, in combination with IoT/Cloud technologies, are fundamentally changing any domain-specific industry. Development of this field is very important because it can help to enhance human life by the automation system, which in turn has far-reaching effects for economic, psychological, educational and organizational improvements to the way we work, teach, learn and care for ourselves and each other"--
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Designed with beginners in mind, this workshop helps you make the most of Python libraries and the Jupyter Notebook's functionality to understand how data science can be applied to solve real-world data problems. Key Features Gain useful insights into data science and machine learning Explore the different functionalities and features of a Jupyter Notebook Discover how Python libraries are used with Jupyter for data analysis Book Description From banking and manufacturing through to education and entertainment, using data science for business has revolutionized almost every sector in the modern world. It has an important role to play in everything from app development to network security. Taking an interactive approach to learning the fundamentals, this book is ideal for beginners. You'll learn all the best practices and techniques for applying data science in the context of real-world scenarios and examples. Starting with an introduction to data science and machine learning, you'll start by getting to grips with Jupyter functionality and features. You'll use Python libraries like sci-kit learn, pandas, Matplotlib, and Seaborn to perform data analysis and data preprocessing on real-world datasets from within your own Jupyter environment. Progressing through the chapters, you'll train classification models using sci-kit learn, and assess model performance using advanced validation techniques. Towards the end, you'll use Jupyter Notebooks to document your research, build stakeholder reports, and even analyze web performance data. By the end of The Applied Data Science Workshop, you'll be prepared to progress from being a beginner to taking your skills to the next level by confidently applying data science techniques and tools to real-world projects. What you will learn Understand the key opportunities and challenges in data science Use Jupyter for data science tasks such as data analysis and modeling Run exploratory data analysis within a Jupyter Notebook Visualize data with pairwise scatter plots and segmented distribution Assess model performance with advanced validation techniques Parse HTML responses and analyze HTTP requests Who this book is for If you are an aspiring data scientist who wants to build a career in data science or a developer who wants to explore the applications of data science from scratch and analyze data in Jupyter using Python libraries, then this book is for you. Although a brief understanding of Python programming and ...
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This book constitutes the refereed proceedings of the 22st International Symposium on VLSI Design and Test, VDAT 2018, held in Madurai, India, in June 2018. The 39 full papers and 11 short papers presented together with 8 poster papers were carefully reviewed and selected from 231 submissions. The papers are organized in topical sections named: digital design; analog and mixed signal design; hardware security; micro bio-fluidics; VLSI testing; analog circuits and devices; network-on-chip; memory; quantum computing and NoC; sensors and interfaces.
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Realizability theory for continuous linear systems
Computer Science / IT. --- System analysis. --- Linear systems. --- Operator theory. --- Functional analysis. --- Functional calculus --- Calculus of variations --- Functional equations --- Integral equations --- Functional analysis --- Network analysis --- Network science --- Network theory --- Systems analysis --- System theory --- Mathematical optimization
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You've heard the hype about Hadoop: it runs petabyte–scale data mining tasks insanely fast, it runs gigantic tasks on clouds for absurdly cheap, it's been heavily committed to by tech giants like IBM, Yahoo!, and the Apache Project, and it's completely open-source (thus free). But what exactly is it, and more importantly, how do you even get a Hadoop cluster up and running? From Apress, the name you've come to trust for hands–on technical knowledge, Pro Hadoop brings you up to speed on Hadoop. You learn the ins and outs of MapReduce; how to structure a cluster, design, and implement the Hadoop file system; and how to build your first cloud–computing tasks using Hadoop. Learn how to let Hadoop take care of distributing and parallelizing your software—you just focus on the code, Hadoop takes care of the rest. Best of all, you'll learn from a tech professional who's been in the Hadoop scene since day one. Written from the perspective of a principal engineer with down–in–the–trenches knowledge of what to do wrong with Hadoop, you learn how to avoid the common, expensive first errors that everyone makes with creating their own Hadoop system or inheriting someone else's. Skip the novice stage and the expensive, hard–to–fix mistakes...go straight to seasoned pro on the hottest cloud–computing framework with Pro Hadoop. Your productivity will blow your managers away.
Computer Science -- IT. --- Expert systems (Computer science). --- Software engineering. --- Computer Science --- Engineering & Applied Sciences --- Information Technology --- Computer Science (Hardware & Networks) --- General and Others --- Computer software. --- Hadoop. --- Software, Computer --- Hadoop --- Computer science. --- Computer Science. --- Computer Science, general. --- Informatics --- Science --- Computer systems --- Big data. --- Big Data. --- Software Engineering/Programming and Operating Systems. --- Computer software engineering --- Engineering --- Data sets, Large --- Large data sets --- Data sets
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Gain the technical and business insight needed to plan, deploy, and manage the services provided by the Microsoft Azure cloud. This second edition focuses on improving operational decision tipping points for the professionals leading DevOps and security teams. This will allow you to make an informed decision concerning the workloads appropriate for your growing business in the Azure public cloud. Microsoft Azure starts with an introduction to Azure along with an overview of its architecture services such as IaaS and PaaS. You’ll also take a look into Azure’s data, artificial intelligence, and machine learning services. Moving on, you will cover the planning for and adoption of Azure where you will go through budgeting, cloud economics, and designing a hybrid data center. Along the way, you will work with web apps, network PaaS, virtual machines, and much more. The final section of the book starts with Azure data services and big data with an in-depth discussion of Azure SQL Database, CosmosDB, Azure Data Lakes, and MySQL. You will further see how to migrate on-premises databases to Azure and use data engineering. Next, you will discover the various Azure services for application developers, including Azure DevOps and ASP.NET web apps. Finally, you will go through the machine learning and AI tools in Azure, including Azure Cognitive Services. You will: Apply design guidance and best practices using Microsoft Azure to achieve business growth Create and manage virtual machines Work with AI frameworks to process and analyze data to support business decisions and increase revenue Deploy, publish, and monitor a web app.
Microsoft software. --- Microsoft .NET Framework. --- Data structures (Computer science). --- Microsoft and .NET. --- Data Storage Representation. --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- Electronic data processing --- File organization (Computer science) --- Abstract data types (Computer science) --- Computer software --- Computer Science/IT. --- Windows Azure. --- Microsoft Windows Azure --- Dot Net (Software framework) --- Microsoft .NET --- Microsoft .NET software framework --- .NET Framework
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This book summarizes the research findings presented at the 13th International Joint Conference on Knowledge-Based Software Engineering (JCKBSE 2020), which took place on August 24–26, 2020. JCKBSE 2020 was originally planned to take place in Larnaca, Cyprus. Unfortunately, the COVID-19 pandemic forced it be rescheduled as an online conference. JCKBSE is a well-established, international, biennial conference that focuses on the applications of artificial intelligence in software engineering. The 2020 edition of the conference was organized by Hiroyuki Nakagawa, Graduate School of Information Science and Technology, Osaka University, Japan, and George A. Tsihrintzis and Maria Virvou, Department of Informatics, University of Piraeus, Greece. This research book is a valuable resource for experts and researchers in the field of (knowledge-based) software engineering, as well as general readers in the fields of artificial and computational Intelligence and, more generally, computer science wanting to learn more about the field of (knowledge-based) software engineering and its applications. An extensive list of bibliographic references at the end of each paper helps readers to probe further into the application areas of interest to them. .
Software engineering. --- Computational intelligence. --- Engineering—Data processing. --- Knowledge representation (Information theory) . --- Software Engineering. --- Computational Intelligence. --- Data Engineering. --- Knowledge based Systems. --- Representation of knowledge (Information theory) --- Artificial intelligence --- Information theory --- Intelligence, Computational --- Soft computing --- Computer software engineering --- Engineering --- Computer Science/IT. --- Software engineering
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PAAMS, the International Conference on Practical Applications of Agents and Multi-Agent Systems is an evolution of the International Workshop on Practical Applications of Agents and Multi-Agent Systems. PAAMS is an international yearly tribune to present, to discuss, and to disseminate the latest developments and the most important outcomes related to real-world applications. It provides a unique opportunity to bring multi-disciplinary experts, academics and practitioners together to exchange their experience in the development of Agents and Multi-Agent Systems. This volume presents the papers that have been accepted for the 2011 in the workshops: Workshop on Agents for Ambient Assisted Living, Workshop on Agent-Based Solutions for Manufacturing and Supply Chain, Workshop on Agents and Multi-agent systems for Enterprise Integration.
Computer science -- IT. --- Intelligent agents (Computer software) -- Congresses. --- Multiagent systems. --- Intelligent agents (Computer software) --- Artificial intelligence --- Engineering & Applied Sciences --- Computer Science --- Engineering. --- Artificial intelligence. --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Intelligence, Computational --- Soft computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Artificial Intelligence.
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Zend Enterprise PHP Patterns is the culmination of years of experience in the development of web-based applications designed to help enterprises big and small overcome the challenges of the web-based application world and achieve harmony in not only the architecture of their application, but also the entire process under which that application is created and maintained. Taken directly from real-life experiences in PHP application development, Zend Enterprise PHP Patterns will help you Utilize open source technologies such as PHP and Zend Framework to build robust and easy-to-maintain development infrastructures. Understand Zend Framework and its philosophical approach to building complex yet easy-to-maintain libraries of functionality for your application that can scale with your needs. Benefit through an in-depth discussion of tools and techniques that can significantly enhance your ability to develop code faster, fix bugs, and increase performance.
Application software -- Development. --- Computer Science -- IT. --- PHP (Computer program language). --- PHP (Computer program language) --- Application software --- Computer Science --- Engineering & Applied Sciences --- Development --- Information Technology --- Computer Science (Hardware & Networks) --- Development. --- Personal Home Page (Computer program language) --- Development of application software --- Computer science. --- Computer Science. --- Computer Science, general. --- Programming languages (Electronic computers) --- Computer programming. --- Software engineering. --- Web Development. --- Software Engineering/Programming and Operating Systems. --- Computer software engineering --- Engineering --- Computers --- Electronic computer programming --- Electronic data processing --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Programming
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