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Author: Kevin Schmidt
Publisher: O'Reilly Media
ISBN: 9781449363628
Category : Computers
Languages : en
Pages : 155
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Book Description
Although you don’t need a large computing infrastructure to process massive amounts of data with Apache Hadoop, it can still be difficult to get started. This practical guide shows you how to quickly launch data analysis projects in the cloud by using Amazon Elastic MapReduce (EMR), the hosted Hadoop framework in Amazon Web Services (AWS). Authors Kevin Schmidt and Christopher Phillips demonstrate best practices for using EMR and various AWS and Apache technologies by walking you through the construction of a sample MapReduce log analysis application. Using code samples and example configurations, you’ll learn how to assemble the building blocks necessary to solve your biggest data analysis problems. Get an overview of the AWS and Apache software tools used in large-scale data analysis Go through the process of executing a Job Flow with a simple log analyzer Discover useful MapReduce patterns for filtering and analyzing data sets Use Apache Hive and Pig instead of Java to build a MapReduce Job Flow Learn the basics for using Amazon EMR to run machine learning algorithms Develop a project cost model for using Amazon EMR and other AWS tools
Author: Kevin Schmidt
Publisher: O'Reilly Media
ISBN: 9781449363628
Category : Computers
Languages : en
Pages : 155
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Book Description
Although you don’t need a large computing infrastructure to process massive amounts of data with Apache Hadoop, it can still be difficult to get started. This practical guide shows you how to quickly launch data analysis projects in the cloud by using Amazon Elastic MapReduce (EMR), the hosted Hadoop framework in Amazon Web Services (AWS). Authors Kevin Schmidt and Christopher Phillips demonstrate best practices for using EMR and various AWS and Apache technologies by walking you through the construction of a sample MapReduce log analysis application. Using code samples and example configurations, you’ll learn how to assemble the building blocks necessary to solve your biggest data analysis problems. Get an overview of the AWS and Apache software tools used in large-scale data analysis Go through the process of executing a Job Flow with a simple log analyzer Discover useful MapReduce patterns for filtering and analyzing data sets Use Apache Hive and Pig instead of Java to build a MapReduce Job Flow Learn the basics for using Amazon EMR to run machine learning algorithms Develop a project cost model for using Amazon EMR and other AWS tools
Author: Thierry Vialar
Publisher: BoD - Books on Demand
ISBN: 2955199001
Category : Mathematics
Languages : en
Pages : 1134
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Book Description
The book consists of XI Parts and 28 Chapters covering all areas of mathematics. It is a tool for students, scientists, engineers, students of many disciplines, teachers, professionals, writers and also for a general reader with an interest in mathematics and in science. It provides a wide range of mathematical concepts, definitions, propositions, theorems, proofs, examples, and numerous illustrations. The difficulty level can vary depending on chapters, and sustained attention will be required for some. The structure and list of Parts are quite classical: I. Foundations of Mathematics, II. Algebra, III. Number Theory, IV. Geometry, V. Analytic Geometry, VI. Topology, VII .Algebraic Topology, VIII. Analysis, IX. Category Theory, X. Probability and Statistics, XI. Applied Mathematics. Appendices provide useful lists of symbols and tables for ready reference. The publisher’s hope is that this book, slightly revised and in a convenient format, will serve the needs of readers, be it for study, teaching, exploration, work, or research.
Author: Chuck Easttom
Publisher: CRC Press
ISBN: 1000907120
Category : Computers
Languages : en
Pages : 306
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Book Description
This book addresses the growing need for machine learning and data mining in neuroscience. The book offers a basic overview of the neuroscience, machine learning and the required math and programming necessary to develop reliable working models. The material is presented in a easy to follow user-friendly manner and is replete with fully working machine learning code. Machine Learning for Neuroscience: A Systematic Approach, tackles the needs of neuroscience researchers and practitioners that have very little training relevant to machine learning. The first section of the book provides an overview of necessary topics in order to delve into machine learning, including basic linear algebra and Python programming. The second section provides an overview of neuroscience and is directed to the computer science oriented readers. The section covers neuroanatomy and physiology, cellular neuroscience, neurological disorders and computational neuroscience. The third section of the book then delves into how to apply machine learning and data mining to neuroscience and provides coverage of artificial neural networks (ANN), clustering, and anomaly detection. The book contains fully working code examples with downloadable working code. It also contains lab assignments and quizzes, making it appropriate for use as a textbook. The primary audience is neuroscience researchers who need to delve into machine learning, programmers assigned neuroscience related machine learning projects and students studying methods in computational neuroscience.
Author: Pranav Shukla
Publisher: Packt Publishing Ltd
ISBN: 1789958539
Category : Computers
Languages : en
Pages : 461
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Book Description
A beginner's guide to storing, managing, and analyzing data with the updated features of Elastic 7.0 Key FeaturesGain access to new features and updates introduced in Elastic Stack 7.0Grasp the fundamentals of Elastic Stack including Elasticsearch, Logstash, and KibanaExplore useful tips for using Elastic Cloud and deploying Elastic Stack in production environmentsBook Description The Elastic Stack is a powerful combination of tools for techniques such as distributed search, analytics, logging, and visualization of data. Elastic Stack 7.0 encompasses new features and capabilities that will enable you to find unique insights into analytics using these techniques. This book will give you a fundamental understanding of what the stack is all about, and help you use it efficiently to build powerful real-time data processing applications. The first few sections of the book will help you understand how to set up the stack by installing tools, and exploring their basic configurations. You’ll then get up to speed with using Elasticsearch for distributed searching and analytics, Logstash for logging, and Kibana for data visualization. As you work through the book, you will discover the technique of creating custom plugins using Kibana and Beats. This is followed by coverage of the Elastic X-Pack, a useful extension for effective security and monitoring. You’ll also find helpful tips on how to use Elastic Cloud and deploy Elastic Stack in production environments. By the end of this book, you’ll be well versed with the fundamental Elastic Stack functionalities and the role of each component in the stack to solve different data processing problems. What you will learnInstall and configure an Elasticsearch architectureSolve the full-text search problem with ElasticsearchDiscover powerful analytics capabilities through aggregations using ElasticsearchBuild a data pipeline to transfer data from a variety of sources into Elasticsearch for analysisCreate interactive dashboards for effective storytelling with your data using KibanaLearn how to secure, monitor and use Elastic Stack’s alerting and reporting capabilitiesTake applications to an on-premise or cloud-based production environment with Elastic StackWho this book is for This book is for entry-level data professionals, software engineers, e-commerce developers, and full-stack developers who want to learn about Elastic Stack and how the real-time processing and search engine works for business analytics and enterprise search applications. Previous experience with Elastic Stack is not required, however knowledge of data warehousing and database concepts will be helpful.
Author: Anurag Srivastava
Publisher: Packt Publishing Ltd
ISBN: 1788834038
Category : Computers
Languages : en
Pages : 365
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Book Description
Get to grips with Kibana and its advanced functions to create interactive visualizations and dashboards Key Features Explore visualizations and perform histograms, stats, and map analytics Unleash X-Pack and Timelion, and learn alerting, monitoring, and reporting features Manage dashboards with Beats and create machine learning jobs for faster analytics Book Description Kibana is one of the popular tools among data enthusiasts for slicing and dicing large datasets and uncovering Business Intelligence (BI) with the help of its rich and powerful visualizations. To begin with, Mastering Kibana 6.x quickly introduces you to the features of Kibana 6.x, before teaching you how to create smart dashboards in no time. You will explore metric analytics and graph exploration, followed by understanding how to quickly customize Kibana dashboards. In addition to this, you will learn advanced analytics such as maps, hits, and list analytics. All this will help you enhance your skills in running and comparing multiple queries and filters, influencing your data visualization skills at scale. With Kibana’s Timelion feature, you can analyze time series data with histograms and stats analytics. By the end of this book, you will have created a speedy machine learning job using X-Pack capabilities. What you will learn Create unique dashboards with various intuitive data visualizations Visualize Timelion expressions with added histograms and stats analytics Integrate X-Pack with your Elastic Stack in simple steps Extract data from Elasticsearch for advanced analysis and anomaly detection using dashboards Build dashboards from web applications for application logs Create monitoring and alerting dashboards using Beats Who this book is for Mastering Kibana 6.x is for you if you are a big data engineer, DevOps engineer, or data scientist aspiring to go beyond data visualization at scale and gain maximum insights from their large datasets. Basic knowledge of Elasticstack will be an added advantage, although not mandatory.
Author: Huage Chen
Publisher: Packt Publishing Ltd
ISBN: 1837633509
Category : Computers
Languages : en
Pages : 688
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Book Description
Unlock the full potential of Elastic Stack for search, analytics, security, and observability and manage substantial data workloads in both on-premise and cloud environments Key Features Explore the diverse capabilities of the Elastic Stack through a comprehensive set of recipes Build search applications, analyze your data, and observe cloud-native applications Harness powerful machine learning and AI features to create data science and search applications Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionLearn how to make the most of the Elastic Stack (ELK Stack) products—including Elasticsearch, Kibana, Elastic Agent, and Logstash—to take data reliably and securely from any source, in any format, and then search, analyze, and visualize it in real-time. This cookbook takes a practical approach to unlocking the full potential of Elastic Stack through detailed recipes step by step. Starting with installing and ingesting data using Elastic Agent and Beats, this book guides you through data transformation and enrichment with various Elastic components and explores the latest advancements in search applications, including semantic search and Generative AI. You'll then visualize and explore your data and create dashboards using Kibana. As you progress, you'll advance your skills with machine learning for data science, get to grips with natural language processing, and discover the power of vector search. The book covers Elastic Observability use cases for log, infrastructure, and synthetics monitoring, along with essential strategies for securing the Elastic Stack. Finally, you'll gain expertise in Elastic Stack operations to effectively monitor and manage your system.What you will learn Discover techniques for collecting data from diverse sources Visualize data and create dashboards using Kibana to extract business insights Explore machine learning, vector search, and AI capabilities of Elastic Stack Handle data transformation and data formatting Build search solutions from the ingested data Leverage data science tools for in-depth data exploration Monitor and manage your system with Elastic Stack Who this book is for This book is for Elastic Stack users, developers, observability practitioners, and data professionals ranging from beginner to expert level. If you’re a developer, you’ll benefit from the easy-to-follow recipes for using APIs and features to build powerful applications, and if you’re an observability practitioner, this book will help you with use cases covering APM, Kubernetes, and cloud monitoring. For data engineers and AI enthusiasts, the book covers dedicated recipes on vector search and machine learning. No prior knowledge of the Elastic Stack is required.
Author: Asjad Athick
Publisher: Packt Publishing Ltd
ISBN: 1800564104
Category : Computers
Languages : en
Pages : 474
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Book Description
Use the Elastic Stack for search, security, and observability-related use cases while working with large amounts of data on-premise and on the cloud Key FeaturesLearn the core components of the Elastic Stack and how they work togetherBuild search experiences, monitor and observe your environments, and defend your organization from cyber attacksGet to grips with common architecture patterns and best practices for successfully deploying the Elastic StackBook Description The Elastic Stack helps you work with massive volumes of data to power use cases in the search, observability, and security solution areas. This three-part book starts with an introduction to the Elastic Stack with high-level commentary on the solutions the stack can be leveraged for. The second section focuses on each core component, giving you a detailed understanding of the component and the role it plays. You'll start by working with Elasticsearch to ingest, search, analyze, and store data for your use cases. Next, you'll look at Logstash, Beats, and Elastic Agent as components that can collect, transform, and load data. Later chapters help you use Kibana as an interface to consume Elastic solutions and interact with data on Elasticsearch. The last section explores the three main use cases offered on top of the Elastic Stack. You'll start with a full-text search and look at real-world outcomes powered by search capabilities. Furthermore, you'll learn how the stack can be used to monitor and observe large and complex IT environments. Finally, you'll understand how to detect, prevent, and respond to security threats across your environment. The book ends by highlighting architecture best practices for successful Elastic Stack deployments. By the end of this book, you'll be able to implement the Elastic Stack and derive value from it. What you will learnConfigure Elasticsearch clusters with different node types for various architecture patternsIngest different data sources into Elasticsearch using Logstash, Beats, and Elastic AgentBuild use cases on Kibana including data visualizations, dashboards, machine learning jobs, and alertsDesign powerful search experiences on top of your data using the Elastic StackSecure your organization and learn how the Elastic SIEM and Endpoint Security capabilities can helpExplore common architectural considerations for accommodating more complex requirementsWho this book is for Developers and solutions architects looking to get hands-on experience with search, security, and observability-related use cases on the Elastic Stack will find this book useful. This book will also help tech leads and product owners looking to understand the value and outcomes they can derive for their organizations using Elastic technology. No prior knowledge of the Elastic Stack is required.
Author: Olivas, Emilio Soria
Publisher: IGI Global
ISBN: 1605667676
Category : Computers
Languages : en
Pages : 852
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Book Description
"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.
Author: H.L. Granzier
Publisher: Springer Science & Business Media
ISBN: 1461542677
Category : Science
Languages : en
Pages : 427
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Book Description
Elastic filaments refer mainly to titin, the largest of all known proteins. Titin was discovered initially in muscle cells, where it interconnects the thick filament with the Z-line. Titin forms a molecular spring that is responsible for maintaining the structural integrity of contracting muscle, ensuring efficient muscle contraction. More recently, it has become clear that titin is not restricted to muscle cells alone. For example, titin is found in chromosomes of neurons and also in blood platelets. This topic is fast becoming a focal point for research in understanding viscoelastic properties at the molecular, cellular, and tissue levels. In titin may lie a generic basis for biological viscoelasticity. It has become clear that titin may hold the key to certain clinical anomalies. For example, it is clear that titin-based ventricular stiffness is modulated by calcium and that titin is responsible for the altered stiffness in cardiomyopathies. It is also clear from evidence from a group of Finnish families that titin mutations may underlie some muscular dystrophies and that with other mutations chromatids fail to separate during mitosis. Thus, it is clear that this protein will have important clinical implications stemming from its biomechanical role. One aspect of this field is the bringing together of bioengineers with clinical researchers and biologists. Genetic and biochemical aspects of titin-related proteins are being studied together with front-line engineering approaches designed to measure the mechanics of titin either in small aggregates or in single molecules.
Author: Thomas H. Courtney
Publisher: Waveland Press
ISBN: 1478608382
Category : Technology & Engineering
Languages : en
Pages : 750
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Book Description
This outstanding text offers a comprehensive treatment of the principles of the mechanical behavior of materials. Appropriate for senior and graduate courses, it is distinguished by its focus on the relationship between macroscopic properties, material microstructure, and fundamental concepts of bonding and crystal structure. The current, second edition retains the original editions extensive coverage of nonmetallics while increasing coverage of ceramics, composites, and polymers that have emerged as structural materials in their own right and are now competitive with metals in many applications. It contains new case studies, includes solved example problems, and incorporates real-life examples. Because of the books extraordinary breadth and depth, adequate coverage of all of the material requires two full semesters of a typical three-credit course. Since most curricula do not have the luxury of allocating this amount of time to mechanical behavior of materials, the text has been designed so that material can be culled or deleted with ease. Instructors can select topics they wish to emphasize and are able to proceed at any level they consider appropriate.
