ICS is a biennial symposium founded in and offers a platform for researchers, educators and professionals to exchange their discoveries and practices, to share research experiences and to discuss potential new trends in the ICT industry. There was also a workshop on information technology innovation, industrial application and the Internet of Things.
ICS is one of Taiwan's most prestigious international IT symposiums, and this book will be of interest to all those involved in the world of information technology. Solutions to common problems when working with the Hadoop ecosystem.
Step-by-step implementation of end-to-end big data use cases. Who This Book Is For Readers who have a basic knowledge of big data systems and want to advance their knowledge with hands-on recipes. X cluster and its ecosystem. Write advanced Map Reduce programs and understand design patterns. Import and export data from various sources using Sqoop and Flume. Machine learning principles with libraries such as Mahout Batch and Stream data processing using Apache Spark In Detail Big data is the current requirement.
Most organizations produce huge amount of data every day. With the arrival of Hadoop-like tools, it has become easier for everyone to solve big data problems with great efficiency and at minimal cost.
Grasping Machine Learning techniques will help you greatly in building predictive models and using this data to make the right decisions for your organization. Hadoop Real World Solutions Cookbook gives readers insights into learning and mastering big data via recipes. The book not only clarifies most big data tools in the market but also provides best practices for using them. The book provides recipes that are based on the latest versions of Apache Hadoop 2.
This real-world-solution cookbook is packed with handy recipes you can apply to your own everyday issues. Each chapter provides in-depth recipes that can be referenced easily. Readers will be able to consider themselves as big data experts on completion of this book. This guide is an invaluable tutorial if you are planning to implement a big data warehouse for your business. Style and approach An easy-to-follow guide that walks you through world of big data.
Each tool in the Hadoop ecosystem is explained in detail and the recipes are placed in such a manner that readers can implement them sequentially. Plenty of reference links are provided for advanced reading. This book dwells on all the aspects of Big Data Analytics and covers the subject in its entirety. The book will serve the interests of undergraduate and post graduate students of computer science and engineering, information technology, and related disciplines.
It will also be useful to software developers. Salient Features: - Comprehensive coverage on Big Data NoSQL Column-family, Object and Graph databases, programming with open-source Big Data - Hadoop and Spark ecosystem tools, such as MapReduce, Hive, Pig, Spark, Python, Mahout, Streaming, GraphX - Inclusion of latest topics machine learning, K-NN, predictive-analytics, similar and frequent item sets, clustering, decision-tree, classifiers recommenders, real-time streaming data analytics, graph networks, text, web structure, web-links, social network analytics.
Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.
Author : Siamak Amirghodsi Publisher: Packt Publishing Ltd ISBN: Category: Computers Page: View: Read Now » Simplify machine learning model implementations with Spark About This Book Solve the day-to-day problems of data science with Spark This unique cookbook consists of exciting and intuitive numerical recipes Optimize your work by acquiring, cleaning, analyzing, predicting, and visualizing your data Who This Book Is For This book is for Scala developers with a fairly good exposure to and understanding of machine learning techniques, but lack practical implementations with Spark.
A solid knowledge of machine learning algorithms is assumed, as well as hands-on experience of implementing ML algorithms with Scala. However, you do not need to be acquainted with the Spark ML libraries and ecosystem. What You Will Learn Get to know how Scala and Spark go hand-in-hand for developers when developing ML systems with Spark Build a recommendation engine that scales with Spark Find out how to build unsupervised clustering systems to classify data in Spark Build machine learning systems with the Decision Tree and Ensemble models in Spark Deal with the curse of high-dimensionality in big data using Spark Implement Text analytics for Search Engines in Spark Streaming Machine Learning System implementation using Spark In Detail Machine learning aims to extract knowledge from data, relying on fundamental concepts in computer science, statistics, probability, and optimization.
Learning about algorithms enables a wide range of applications, from everyday tasks such as product recommendations and spam filtering to cutting edge applications such as self-driving cars and personalized medicine. You will gain hands-on experience of applying these principles using Apache Spark, a resilient cluster computing system well suited for large-scale machine learning tasks.
This book begins with a quick overview of setting up the necessary IDEs to facilitate the execution of code examples that will be covered in various chapters. It also highlights some key issues developers face while working with machine learning algorithms on the Spark platform.
We progress by uncovering the various Spark APIs and the implementation of ML algorithms with developing classification systems, recommendation engines, text analytics, clustering, and learning systems.
Toward the final chapters, we'll focus on building high-end applications and explain various unsupervised methodologies and challenges to tackle when implementing with big data ML systems.
Style and approach This book is packed with intuitive recipes supported with line-by-line explanations to help you understand how to optimize your work flow and resolve problems when working with complex data modeling tasks and predictive algorithms. This is a valuable resource for data scientists and those working on large scale data projects. It support multiple programming languages like Java, Scala, Python and R. Hence, many existing and new framework started to integrate Spark platform as well in their platform e.
Hadoop, Cassandra, EMR etc. While creating Spark certification material HadoopExam technical team found that there is no proper material and book is available for the Spark SQL version 2. Therefore, they decided to create full length book for Spark SQL and outcome of that is this book.
In this book technical team try to cover both fundamental concepts of Spark SQL engine and many exercises approx. There are approximately 35 exercises and total 15 chapters which covers the programming aspects of SparkSQL. You are not required to have HBase experience, but are expected to have a basic understanding of Hadoop and MapReduce.
Written in the cookbook style, this book offers learning and techniques through recipes. It contains step-by-step instructions for administrators and developers to manage databases on PostgreSQL. The book is designed in such a way that you can read it chapter by chapter or refer to recipes in no particular order. This book is for Sysadmins, Database Administrators, Architects, Developers, and anyone with an interest in planning for or running live production databases.
This book is most suited to those who have some technical experience Oracle Enterprise Manager 12c Administration Cookbook. Over 50 practical recipes to install, configure, and monitor your Oracle setup using Oracle Enterprise Manager Overview Recipes for installing, configuring, and getting up and running with Oracle Enterprise Manager.
Set up automatic discovery, create and clone databases, and perform provisioning. In Detail Oracle Enterprise Manager is a key tool for any Oracle Administrator, allowing them to manage their Oracle installations and selected other applications, providing a one stop place to manage and maintain the entire infrastructure in any organization.
The Oracle Enterprise Manager 12c Cookbook will give administrators a head start towards impleme Microsoft SharePoint Administration Cookbook. Microsoft SharePoint Administration Cookbook contains step-by-step instructions for SharePoint administrators to gain control of their SharePoint environment. The book is designed so that you can refer to it chapter by chapter, or you can look at the list of recipes and read those that interest you in no particular order.
If you are a SharePoint Administrator looking for solutions to the many problems faced while managing SharePoint, then this book is for you.
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