Apache Spark Machine Learning Blueprints

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Apache Spark Machine Learning Blueprints

Author : Alex Liu
Publisher : Packt Publishing Ltd
ISBN 13 : 1785887785
Total Pages : 252 pages
Book Rating : 4.7/5 (858 download)

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Book Synopsis Apache Spark Machine Learning Blueprints by : Alex Liu

Download or read book Apache Spark Machine Learning Blueprints written by Alex Liu and published by Packt Publishing Ltd. This book was released on 2016-05-30 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop a range of cutting-edge machine learning projects with Apache Spark using this actionable guide About This Book Customize Apache Spark and R to fit your analytical needs in customer research, fraud detection, risk analytics, and recommendation engine development Develop a set of practical Machine Learning applications that can be implemented in real-life projects A comprehensive, project-based guide to improve and refine your predictive models for practical implementation Who This Book Is For If you are a data scientist, a data analyst, or an R and SPSS user with a good understanding of machine learning concepts, algorithms, and techniques, then this is the book for you. Some basic understanding of Spark and its core elements and application is required. What You Will Learn Set up Apache Spark for machine learning and discover its impressive processing power Combine Spark and R to unlock detailed business insights essential for decision making Build machine learning systems with Spark that can detect fraud and analyze financial risks Build predictive models focusing on customer scoring and service ranking Build a recommendation systems using SPSS on Apache Spark Tackle parallel computing and find out how it can support your machine learning projects Turn open data and communication data into actionable insights by making use of various forms of machine learning In Detail There's a reason why Apache Spark has become one of the most popular tools in Machine Learning – its ability to handle huge datasets at an impressive speed means you can be much more responsive to the data at your disposal. This book shows you Spark at its very best, demonstrating how to connect it with R and unlock maximum value not only from the tool but also from your data. Packed with a range of project "blueprints" that demonstrate some of the most interesting challenges that Spark can help you tackle, you'll find out how to use Spark notebooks and access, clean, and join different datasets before putting your knowledge into practice with some real-world projects, in which you will see how Spark Machine Learning can help you with everything from fraud detection to analyzing customer attrition. You'll also find out how to build a recommendation engine using Spark's parallel computing powers. Style and approach This book offers a step-by-step approach to setting up Apache Spark, and use other analytical tools with it to process Big Data and build machine learning projects.The initial chapters focus more on the theory aspect of machine learning with Spark, while each of the later chapters focuses on building standalone projects using Spark.

Apache Spark Machine Learning Blueprints

Author : Alex Liu
Publisher : Packt Publishing Ltd
ISBN 13 : 1785887785
Total Pages : 252 pages
Book Rating : 4.7/5 (858 download)

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Book Synopsis Apache Spark Machine Learning Blueprints by : Alex Liu

Hadoop Blueprints

Author : Anurag Shrivastava
Publisher : Packt Publishing Ltd
ISBN 13 : 1783980311
Total Pages : 312 pages
Book Rating : 4.7/5 (839 download)

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Book Synopsis Hadoop Blueprints by : Anurag Shrivastava

Download or read book Hadoop Blueprints written by Anurag Shrivastava and published by Packt Publishing Ltd. This book was released on 2016-09-30 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use Hadoop to solve business problems by learning from a rich set of real-life case studies About This Book Solve real-world business problems using Hadoop and other Big Data technologies Build efficient data lakes in Hadoop, and develop systems for various business cases like improving marketing campaigns, fraud detection, and more Power packed with six case studies to get you going with Hadoop for Business Intelligence Who This Book Is For If you are interested in building efficient business solutions using Hadoop, this is the book for you This book assumes that you have basic knowledge of Hadoop, Java, and any scripting language. What You Will Learn Learn about the evolution of Hadoop as the big data platform Understand the basics of Hadoop architecture Build a 360 degree view of your customer using Sqoop and Hive Build and run classification models on Hadoop using BigML Use Spark and Hadoop to build a fraud detection system Develop a churn detection system using Java and MapReduce Build an IoT-based data collection and visualization system Get to grips with building a Hadoop-based Data Lake for large enterprises Learn about the coexistence of NoSQL and In-Memory databases in the Hadoop ecosystem In Detail If you have a basic understanding of Hadoop and want to put your knowledge to use to build fantastic Big Data solutions for business, then this book is for you. Build six real-life, end-to-end solutions using the tools in the Hadoop ecosystem, and take your knowledge of Hadoop to the next level. Start off by understanding various business problems which can be solved using Hadoop. You will also get acquainted with the common architectural patterns which are used to build Hadoop-based solutions. Build a 360-degree view of the customer by working with different types of data, and build an efficient fraud detection system for a financial institution. You will also develop a system in Hadoop to improve the effectiveness of marketing campaigns. Build a churn detection system for a telecom company, develop an Internet of Things (IoT) system to monitor the environment in a factory, and build a data lake – all making use of the concepts and techniques mentioned in this book. The book covers other technologies and frameworks like Apache Spark, Hive, Sqoop, and more, and how they can be used in conjunction with Hadoop. You will be able to try out the solutions explained in the book and use the knowledge gained to extend them further in your own problem space. Style and approach This is an example-driven book where each chapter covers a single business problem and describes its solution by explaining the structure of a dataset and tools required to process it. Every project is demonstrated with a step-by-step approach, and explained in a very easy-to-understand manner.

Transforming Healthcare with Big Data and AI

Author : Alex Liu
Publisher : IAP
ISBN 13 : 1641138998
Total Pages : 184 pages
Book Rating : 4.6/5 (411 download)

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Book Synopsis Transforming Healthcare with Big Data and AI by : Alex Liu

Download or read book Transforming Healthcare with Big Data and AI written by Alex Liu and published by IAP. This book was released on 2020-04-01 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare and technology are at a convergence point where significant changes are poised to take place. The vast and complex requirements of medical record keeping, coupled with stringent patient privacy laws, create an incredibly unwieldy maze of health data needs. While the past decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be accumulated, processed, and shared around the globe. Transforming Healthcare with Big Data and AI examines the crossroads of these two fields and looks to the future of leveraging advanced technologies and developing data ecosystems to the healthcare field. This book is the product of the Transforming Healthcare with Data conference, held at the University of Southern California. Many speakers and digital healthcare industry leaders contributed multidisciplinary expertise to chapters in this work. Authors’ backgrounds range from data scientists, healthcare experts, university professors, and digital healthcare entrepreneurs. If you have an understanding of data technologies and are interested in the future of Big Data and A.I. in healthcare, this book will provide a wealth of insights into the new landscape of healthcare.

Strategic Blueprint for Enterprise Analytics

Author : Liang Wang
Publisher : Springer Nature
ISBN 13 : 3031558855
Total Pages : 256 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Strategic Blueprint for Enterprise Analytics by : Liang Wang

Download or read book Strategic Blueprint for Enterprise Analytics written by Liang Wang and published by Springer Nature. This book was released on with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Learn Azure Synapse Data Explorer

Author : Pericles (Peri) Rocha
Publisher : Packt Publishing Ltd
ISBN 13 : 1803239611
Total Pages : 346 pages
Book Rating : 4.8/5 (32 download)

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Book Synopsis Learn Azure Synapse Data Explorer by : Pericles (Peri) Rocha

Download or read book Learn Azure Synapse Data Explorer written by Pericles (Peri) Rocha and published by Packt Publishing Ltd. This book was released on 2023-02-17 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on guide to working on use cases helping you ingest, analyze, and serve insightful data from IoT as well as telemetry data sources using Azure Synapse Data Explorer Free PDF included with this book Key FeaturesAugment advanced analytics projects with your IoT and application dataExpand your existing Azure Synapse environments with unstructured dataBuild industry-level projects on integration, experimentation, and dashboarding with Azure SynapseBook Description Large volumes of data are generated daily from applications, websites, IoT devices, and other free-text, semi-structured data sources. Azure Synapse Data Explorer helps you collect, store, and analyze such data, and work with other analytical engines, such as Apache Spark, to develop advanced data science projects and maximize the value you extract from data. This book offers a comprehensive view of Azure Synapse Data Explorer, exploring not only the core scenarios of Data Explorer but also how it integrates within Azure Synapse. From data ingestion to data visualization and advanced analytics, you'll learn to take an end-to-end approach to maximize the value of unstructured data and drive powerful insights using data science capabilities. With real-world usage scenarios, you'll discover how to identify key projects where Azure Synapse Data Explorer can help you achieve your business goals. Throughout the chapters, you'll also find out how to manage big data as part of a software as a service (SaaS) platform, as well as tune, secure, and serve data to end users. By the end of this book, you'll have mastered the big data life cycle and you'll be able to implement advanced analytical scenarios from raw telemetry and log data. What you will learnIntegrate Data Explorer pools with all other Azure Synapse servicesCreate Data Explorer pools with Azure Synapse Studio and Azure PortalIngest, analyze, and serve data to users using Azure Synapse pipelinesIntegrate Power BI and visualize data with Synapse StudioConfigure Azure Machine Learning integration in Azure SynapseManage cost and troubleshoot Data Explorer pools in Synapse AnalyticsSecure Synapse workspaces and grant access to Data Explorer poolsWho this book is for If you are a data engineer, data analyst, or business analyst working with unstructured data and looking to learn how to maximize the value of such data, this book is for you. If you already have experience working with Azure Synapse and want to incorporate unstructured data into your data science project, you'll also find plenty of useful information in this book. To maximize your learning experience, familiarity with data and performing simple queries using SQL or KQL is recommended. Basic knowledge of Python will help you get more from the examples.

Stream Processing with Apache Spark

Author : Gerard Maas
Publisher : O'Reilly Media
ISBN 13 : 1491944218
Total Pages : 453 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Stream Processing with Apache Spark by : Gerard Maas

Download or read book Stream Processing with Apache Spark written by Gerard Maas and published by O'Reilly Media. This book was released on 2019-06-05 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: Before you can build analytics tools to gain quick insights, you first need to know how to process data in real time. With this practical guide, developers familiar with Apache Spark will learn how to put this in-memory framework to use for streaming data. You’ll discover how Spark enables you to write streaming jobs in almost the same way you write batch jobs. Authors Gerard Maas and François Garillot help you explore the theoretical underpinnings of Apache Spark. This comprehensive guide features two sections that compare and contrast the streaming APIs Spark now supports: the original Spark Streaming library and the newer Structured Streaming API. Learn fundamental stream processing concepts and examine different streaming architectures Explore Structured Streaming through practical examples; learn different aspects of stream processing in detail Create and operate streaming jobs and applications with Spark Streaming; integrate Spark Streaming with other Spark APIs Learn advanced Spark Streaming techniques, including approximation algorithms and machine learning algorithms Compare Apache Spark to other stream processing projects, including Apache Storm, Apache Flink, and Apache Kafka Streams

Automated Machine Learning for Business

Author : Kai R. Larsen
Publisher : Oxford University Press
ISBN 13 : 0190941650
Total Pages : 353 pages
Book Rating : 4.1/5 (99 download)

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Book Synopsis Automated Machine Learning for Business by : Kai R. Larsen

Download or read book Automated Machine Learning for Business written by Kai R. Larsen and published by Oxford University Press. This book was released on 2021 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book teaches the full process of how to conduct machine learning in an organizational setting. It develops the problem-solving mind-set needed for machine learning and takes the reader through several exercises using an automated machine learning tool. To build experience with machine learning, the book provides access to the industry-leading AutoML tool, DataRobot, and provides several data sets designed to build deep hands-on knowledge of machinelearning.

Unreal Engine 4 Virtual Reality Projects

Author : Kevin Mack
Publisher : Packt Publishing Ltd
ISBN 13 : 1789133882
Total Pages : 622 pages
Book Rating : 4.7/5 (891 download)

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Book Synopsis Unreal Engine 4 Virtual Reality Projects by : Kevin Mack

Download or read book Unreal Engine 4 Virtual Reality Projects written by Kevin Mack and published by Packt Publishing Ltd. This book was released on 2019-04-30 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: The key problem with VR development is understanding how to set up a project and running it on your desktop or mobile VR device. With this book, you will not only learn the specifics of virtual reality development in Unreal but also build immersive and fun VR projects that can be experienced on your VR devices.

Cloud Computing for Machine Learning and Cognitive Applications

Author : Kai Hwang
Publisher : MIT Press
ISBN 13 : 026203641X
Total Pages : 626 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Cloud Computing for Machine Learning and Cognitive Applications by : Kai Hwang

Download or read book Cloud Computing for Machine Learning and Cognitive Applications written by Kai Hwang and published by MIT Press. This book was released on 2017-06-16 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first textbook to teach students how to build data analytic solutions on large data sets using cloud-based technologies. This is the first textbook to teach students how to build data analytic solutions on large data sets (specifically in Internet of Things applications) using cloud-based technologies for data storage, transmission and mashup, and AI techniques to analyze this data. This textbook is designed to train college students to master modern cloud computing systems in operating principles, architecture design, machine learning algorithms, programming models and software tools for big data mining, analytics, and cognitive applications. The book will be suitable for use in one-semester computer science or electrical engineering courses on cloud computing, machine learning, cloud programming, cognitive computing, or big data science. The book will also be very useful as a reference for professionals who want to work in cloud computing and data science. Cloud and Cognitive Computing begins with two introductory chapters on fundamentals of cloud computing, data science, and adaptive computing that lay the foundation for the rest of the book. Subsequent chapters cover topics including cloud architecture, mashup services, virtual machines, Docker containers, mobile clouds, IoT and AI, inter-cloud mashups, and cloud performance and benchmarks, with a focus on Google's Brain Project, DeepMind, and X-Lab programs, IBKai HwangM SyNapse, Bluemix programs, cognitive initiatives, and neurocomputers. The book then covers machine learning algorithms and cloud programming software tools and application development, applying the tools in machine learning, social media, deep learning, and cognitive applications. All cloud systems are illustrated with big data and cognitive application examples.

Actionable Insights with Amazon QuickSight

Author : Manos Samatas
Publisher : Packt Publishing Ltd
ISBN 13 : 1801072000
Total Pages : 242 pages
Book Rating : 4.8/5 (1 download)

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Book Synopsis Actionable Insights with Amazon QuickSight by : Manos Samatas

Download or read book Actionable Insights with Amazon QuickSight written by Manos Samatas and published by Packt Publishing Ltd. This book was released on 2022-01-28 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build interactive dashboards and storytelling reports at scale with the cloud-native BI tool that integrates embedded analytics and ML-powered insights effortlessly Key FeaturesExplore Amazon QuickSight, manage data sources, and build and share dashboardsLearn best practices from an AWS certified big data solutions architect Manage and monitor dashboards using the QuickSight API and other AWS services such as Amazon CloudTrailBook Description Amazon Quicksight is an exciting new visualization that rivals PowerBI and Tableau, bringing several exciting features to the table – but sadly, there aren't many resources out there that can help you learn the ropes. This book seeks to remedy that with the help of an AWS-certified expert who will help you leverage its full capabilities. After learning QuickSight's fundamental concepts and how to configure data sources, you'll be introduced to the main analysis-building functionality of QuickSight to develop visuals and dashboards, and explore how to develop and share interactive dashboards with parameters and on-screen controls. You'll dive into advanced filtering options with URL actions before learning how to set up alerts and scheduled reports. Next, you'll familiarize yourself with the types of insights before getting to grips with adding ML insights such as forecasting capabilities, analyzing time series data, adding narratives, and outlier detection to your dashboards. You'll also explore patterns to automate operations and look closer into the API actions that allow us to control settings. Finally, you'll learn advanced topics such as embedded dashboards and multitenancy. By the end of this book, you'll be well-versed with QuickSight's BI and analytics functionalities that will help you create BI apps with ML capabilities. What you will learnUnderstand the wider AWS analytics ecosystem and how QuickSight fits within itSet up and configure data sources with Amazon QuickSightInclude custom controls and add interactivity to your BI application using parametersAdd ML insights such as forecasting, anomaly detection, and narrativesExplore patterns to automate operations using QuickSight APIsCreate interactive dashboards and storytelling with Amazon QuickSightDesign an embedded multi-tenant analytics architectureFocus on data permissions and how to manage Amazon QuickSight operationsWho this book is for This book is for business intelligence (BI) developers and data analysts who are looking to create interactive dashboards using data from Lake House on AWS with Amazon QuickSight. It will also be useful for anyone who wants to learn Amazon QuickSight in depth using practical, up-to-date examples. You will need to be familiar with general data visualization concepts before you get started with this book, however, no prior experience with Amazon QuickSight is required.

Genomics in the Azure Cloud

Author : Colby T. Ford
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098139011
Total Pages : 330 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Genomics in the Azure Cloud by : Colby T. Ford

Download or read book Genomics in the Azure Cloud written by Colby T. Ford and published by "O'Reilly Media, Inc.". This book was released on 2022-11-14 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical guide bridges the gap between general cloud computing architecture in Microsoft Azure and scientific computing for bioinformatics and genomics. You'll get a solid understanding of the architecture patterns and services that are offered in Azure and how they might be used in your bioinformatics practice. You'll get code examples that you can reuse for your specific needs. And you'll get plenty of concrete examples to illustrate how a given service is used in a bioinformatics context. You'll also get valuable advice on how to: Use enterprise platform services to easily scale your bioinformatics workloads Organize, query, and analyze genomic data at scale Build a genomics data lake and accompanying data warehouse Use Azure Machine Learning to scale your model training, track model performance, and deploy winning models Orchestrate and automate processing pipelines using Azure Data Factory and Databricks Cloudify your organization's existing bioinformatics pipelines by moving your workflows to Azure high-performance compute services And more

Research Anthology on Usage and Development of Open Source Software

Author : Management Association, Information Resources
Publisher : IGI Global
ISBN 13 : 1799891593
Total Pages : 904 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Research Anthology on Usage and Development of Open Source Software by : Management Association, Information Resources

Download or read book Research Anthology on Usage and Development of Open Source Software written by Management Association, Information Resources and published by IGI Global. This book was released on 2021-06-25 with total page 904 pages. Available in PDF, EPUB and Kindle. Book excerpt: The quick growth of computer technology and development of software caused it to be in a constant state of change and advancement. This advancement in software development meant that there would be many types of software developed in order to excel in usability and efficiency. Among these different types of software was open source software, one that grants permission for users to use, study, change, and distribute it freely. Due to its availability, open source software has quickly become a valuable asset to the world of computer technology and across various disciplines including education, business, and library science. The Research Anthology on Usage and Development of Open Source Software presents comprehensive research on the design and development of open source software as well as the ways in which it is used. The text discusses in depth the way in which this computer software has been made into a collaborative effort for the advancement of software technology. Discussing topics such as ISO standards, big data, fault prediction, open collaboration, and software development, this anthology is essential for computer engineers, software developers, IT specialists and consultants, instructors, librarians, managers, executives, professionals, academicians, researchers, and students.

Data Engineering Best Practices

Author : Richard J. Schiller
Publisher : Packt Publishing Ltd
ISBN 13 : 1803247363
Total Pages : 550 pages
Book Rating : 4.8/5 (32 download)

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Book Synopsis Data Engineering Best Practices by : Richard J. Schiller

Download or read book Data Engineering Best Practices written by Richard J. Schiller and published by Packt Publishing Ltd. This book was released on 2024-10-11 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore modern data engineering techniques and best practices to build scalable, efficient, and future-proof data processing systems across cloud platforms Key Features Architect and engineer optimized data solutions in the cloud with best practices for performance and cost-effectiveness Explore design patterns and use cases to balance roles, technology choices, and processes for a future-proof design Learn from experts to avoid common pitfalls in data engineering projects Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionRevolutionize your approach to data processing in the fast-paced business landscape with this essential guide to data engineering. Discover the power of scalable, efficient, and secure data solutions through expert guidance on data engineering principles and techniques. Written by two industry experts with over 60 years of combined experience, it offers deep insights into best practices, architecture, agile processes, and cloud-based pipelines. You’ll start by defining the challenges data engineers face and understand how this agile and future-proof comprehensive data solution architecture addresses them. As you explore the extensive toolkit, mastering the capabilities of various instruments, you’ll gain the knowledge needed for independent research. Covering everything you need, right from data engineering fundamentals, the guide uses real-world examples to illustrate potential solutions. It elevates your skills to architect scalable data systems, implement agile development processes, and design cloud-based data pipelines. The book further equips you with the knowledge to harness serverless computing and microservices to build resilient data applications. By the end, you'll be armed with the expertise to design and deliver high-performance data engineering solutions that are not only robust, efficient, and secure but also future-ready.What you will learn Architect scalable data solutions within a well-architected framework Implement agile software development processes tailored to your organization's needs Design cloud-based data pipelines for analytics, machine learning, and AI-ready data products Optimize data engineering capabilities to ensure performance and long-term business value Apply best practices for data security, privacy, and compliance Harness serverless computing and microservices to build resilient, scalable, and trustworthy data pipelines Who this book is for If you are a data engineer, ETL developer, or big data engineer who wants to master the principles and techniques of data engineering, this book is for you. A basic understanding of data engineering concepts, ETL processes, and big data technologies is expected. This book is also for professionals who want to explore advanced data engineering practices, including scalable data solutions, agile software development, and cloud-based data processing pipelines.

Mastering Azure

Author : Cybellium Ltd
Publisher : Cybellium Ltd
ISBN 13 :
Total Pages : 218 pages
Book Rating : 4.8/5 (591 download)

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Book Synopsis Mastering Azure by : Cybellium Ltd

Download or read book Mastering Azure written by Cybellium Ltd and published by Cybellium Ltd. This book was released on 2023-09-06 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cybellium Ltd is dedicated to empowering individuals and organizations with the knowledge and skills they need to navigate the ever-evolving computer science landscape securely and learn only the latest information available on any subject in the category of computer science including: - Information Technology (IT) - Cyber Security - Information Security - Big Data - Artificial Intelligence (AI) - Engineering - Robotics - Standards and compliance Our mission is to be at the forefront of computer science education, offering a wide and comprehensive range of resources, including books, courses, classes and training programs, tailored to meet the diverse needs of any subject in computer science. Visit https://www.cybellium.com for more books.

Serverless ETL and Analytics with AWS Glue

Author : Vishal Pathak
Publisher : Packt Publishing Ltd
ISBN 13 : 1800562551
Total Pages : 435 pages
Book Rating : 4.8/5 (5 download)

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Book Synopsis Serverless ETL and Analytics with AWS Glue by : Vishal Pathak

Download or read book Serverless ETL and Analytics with AWS Glue written by Vishal Pathak and published by Packt Publishing Ltd. This book was released on 2022-08-30 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build efficient data lakes that can scale to virtually unlimited size using AWS Glue Key Features Book DescriptionOrganizations these days have gravitated toward services such as AWS Glue that undertake undifferentiated heavy lifting and provide serverless Spark, enabling you to create and manage data lakes in a serverless fashion. This guide shows you how AWS Glue can be used to solve real-world problems along with helping you learn about data processing, data integration, and building data lakes. Beginning with AWS Glue basics, this book teaches you how to perform various aspects of data analysis such as ad hoc queries, data visualization, and real-time analysis using this service. It also provides a walk-through of CI/CD for AWS Glue and how to shift left on quality using automated regression tests. You’ll find out how data security aspects such as access control, encryption, auditing, and networking are implemented, as well as getting to grips with useful techniques such as picking the right file format, compression, partitioning, and bucketing. As you advance, you’ll discover AWS Glue features such as crawlers, Lake Formation, governed tables, lineage, DataBrew, Glue Studio, and custom connectors. The concluding chapters help you to understand various performance tuning, troubleshooting, and monitoring options. By the end of this AWS book, you’ll be able to create, manage, troubleshoot, and deploy ETL pipelines using AWS Glue.What you will learn Apply various AWS Glue features to manage and create data lakes Use Glue DataBrew and Glue Studio for data preparation Optimize data layout in cloud storage to accelerate analytics workloads Manage metadata including database, table, and schema definitions Secure your data during access control, encryption, auditing, and networking Monitor AWS Glue jobs to detect delays and loss of data Integrate Spark ML and SageMaker with AWS Glue to create machine learning models Who this book is for ETL developers, data engineers, and data analysts

Machine Learning with Spark

Author : Rajdeep Dua
Publisher : Packt Publishing Ltd
ISBN 13 : 1785886428
Total Pages : 523 pages
Book Rating : 4.7/5 (858 download)

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Book Synopsis Machine Learning with Spark by : Rajdeep Dua

Download or read book Machine Learning with Spark written by Rajdeep Dua and published by Packt Publishing Ltd. This book was released on 2017-04-28 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create scalable machine learning applications to power a modern data-driven business using Spark 2.x About This Book Get to the grips with the latest version of Apache Spark Utilize Spark's machine learning library to implement predictive analytics Leverage Spark's powerful tools to load, analyze, clean, and transform your data Who This Book Is For If you have a basic knowledge of machine learning and want to implement various machine-learning concepts in the context of Spark ML, this book is for you. You should be well versed with the Scala and Python languages. What You Will Learn Get hands-on with the latest version of Spark ML Create your first Spark program with Scala and Python Set up and configure a development environment for Spark on your own computer, as well as on Amazon EC2 Access public machine learning datasets and use Spark to load, process, clean, and transform data Use Spark's machine learning library to implement programs by utilizing well-known machine learning models Deal with large-scale text data, including feature extraction and using text data as input to your machine learning models Write Spark functions to evaluate the performance of your machine learning models In Detail This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML. Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML. By the end of this book, you will acquire the skills to leverage Spark's features to create your own scalable machine learning applications and power a modern data-driven business. Style and approach This practical tutorial with real-world use cases enables you to develop your own machine learning systems with Spark. The examples will help you combine various techniques and models into an intelligent machine learning system.