Páginas: 384 Géneros: 12:UYQ:Artificial intelligence 12:UNC:Data capture & analysis 12:UYQN:Neural networks & fuzzy systems Sinopsis:
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Build next-generation Artificial Intelligence systems with Java Key Features Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Book DescriptionIn this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. What you will learn Manage Artificial Intelligence techniques for big data with Java Build smart systems to analyze data for enhanced customer experience Learn to use Artificial Intelligence frameworks for big data Understand complex problems with algorithms and Neuro-Fuzzy systems Design stratagems to leverage data using Machine Learning process Apply Deep Learning techniques to prepare data for modeling Construct models that learn from data using open source tools Analyze big data problems using scalable Machine Learning algorithms Who this book is forThis book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus.
Anand Deshpande is the Director of big data delivery at Datametica Solutions. He is responsible for partnering with clients on their data strategies and helps them become data-driven. He has extensive experience with big data ecosystem technologies. He has developed a special interest in data science, cognitive intelligence, and an algorithmic approach to data management and analytics. He is a regular speaker on data science and big data at various events. Manish Kumar is a Senior Technical Architect at Datametica Solutions. He has more than 11 years of industry experience in data management as a data, solutions, and product architect. He has extensive experience in building effective ETL pipelines, implementing security over Hadoop, implementing real-time data analytics solutions, and providing innovative and best possible solutions to data science problems. He is a regular speaker on big data and data science.
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A learning guide to get you started with PowerShell DSC. Key Features Create flexible and maintainable deployments using DSC configuration scripts that stand the test of time. Explore the core architecture, concepts, and practices in depth. Learning PowerShell DSC is a step-by-step guide that shows you how to start using and taking advantage of PowerShell DSC along with configuring and deploying applications. Book Description The main goal of this book is to teach you to configure, deploy, and manage your system using the new features of PowerShell v5/v6 DSC. This book begins with the basics of PowerShell Desired State Configuration, covering its architecture and components. It familiarizes you with the set of Windows PowerShell language extensions and new Windows PowerShell commands that make up DSC. Then it helps you create DSC custom resources and work with DSC configurations with the help of practical examples. Finally, it describes how to deploy configuration data using PowerShell DSC. Throughout this book, we will be focusing on concepts such as building configurations with parameters, the local configuration manager, and testing and restoring configurations using PowerShell DSC. By the end of the book, you will be able to deploy a real-world application end-to-end and will be familiar enough with the powerful Desired State Configuration platform to achieve continuous delivery and efficiently and easily manage and deploy data for systems. What You Will Learn Explore PowerShell Desired State Configuration and activities around it, including the need for configuration management and abstraction. Create reusable DSC configurations and debug/ troubleshoot configuration files. Learn about the PowerShell DSC architecture with the help of push-and-pull management and workflows. Define DSC configuration scripts and data files and push DSC configuration files remotely and locally. Validate DSC Pull Server install and register target nodes with a DSC Pull Server. Learn about DSC Cross Platform and install PowerShell on Linux and macOS along with real-life DSC uses and different types of deployment. Who This Book Is For If you are a system administrator, developer, or engineer and are responsible for configuration management and automation, then this book is for you. IT professionals who wish to learn PowerShell Desired State Configuration for the efficient management, configuration, and deployment of systems will also find this book useful. Nº de ref. del artículo: 9781788472173
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