Next Generation Machine Learning With Spark
DOWNLOAD
Download Next Generation Machine Learning With Spark PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Next Generation Machine Learning With Spark book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Next Generation Machine Learning With Spark
DOWNLOAD
Author : Butch Quinto
language : en
Publisher: Apress
Release Date : 2020-02-22
Next Generation Machine Learning With Spark written by Butch Quinto and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-22 with Computers categories.
Access real-world documentation and examples for the Spark platform for building large-scale, enterprise-grade machine learning applications. The past decade has seen an astonishing series of advances in machine learning. These breakthroughs are disrupting our everyday life and making an impact across every industry. Next-Generation Machine Learning with Spark provides a gentle introduction to Spark and Spark MLlib and advances to more powerful, third-party machine learning algorithms and libraries beyond what is available in the standard Spark MLlib library. By the end of this book, you will be able to apply your knowledge to real-world use cases through dozens of practical examples and insightful explanations. What You Will Learn Be introduced to machine learning, Spark, and Spark MLlib 2.4.x Achieve lightning-fast gradient boosting on Spark with the XGBoost4J-Spark and LightGBM libraries Detect anomalies with the Isolation Forest algorithm for Spark Use the Spark NLP and Stanford CoreNLP libraries that support multiple languages Optimize your ML workload with the Alluxio in-memory data accelerator for Spark Use GraphX and GraphFrames for Graph Analysis Perform image recognition using convolutional neural networks Utilize the Keras framework and distributed deep learning libraries with Spark Who This Book Is For Data scientists and machine learning engineers who want to take their knowledge to the next level and use Spark and more powerful, next-generation algorithms and libraries beyond what is available in the standard Spark MLlib library; also serves as a primer for aspiring data scientists and engineers who need an introduction to machine learning, Spark, and Spark MLlib.
Internet Of Things And Big Data Analytics Toward Next Generation Intelligence
DOWNLOAD
Author : Nilanjan Dey
language : en
Publisher: Springer
Release Date : 2017-08-14
Internet Of Things And Big Data Analytics Toward Next Generation Intelligence written by Nilanjan Dey and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-14 with Technology & Engineering categories.
This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments. Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people’s imaginations as to what a fully connected world can offer. Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions. The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies.
Agents And Multi Agent Systems Technologies And Applications 2021
DOWNLOAD
Author : G. Jezic
language : en
Publisher: Springer Nature
Release Date : 2021-06-07
Agents And Multi Agent Systems Technologies And Applications 2021 written by G. Jezic and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-07 with Technology & Engineering categories.
This book highlights new trends and challenges in research on agents and the new digital and knowledge economy. It includes papers on business process management, agent-based modeling and simulation, and anthropic-oriented computing that were originally presented at the 15th International KES Conference on Agents and Multi-Agent Systems: Technologies and Applications (KES-AMSTA 2021), being held as a Virtual Conference in June 14–16, 2021. The respective papers cover topics such as software agents, multi-agent systems, agent modeling, mobile and cloud computing, big data analysis, business intelligence, artificial intelligence, social systems, computer embedded systems, and nature-inspired manufacturing, all of which contribute to the modern digital economy.
Python Deep Learning
DOWNLOAD
Author : Valentino Zocca
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-04-28
Python Deep Learning written by Valentino Zocca and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-28 with Computers categories.
Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python. About This Book Explore and create intelligent systems using cutting-edge deep learning techniques Implement deep learning algorithms and work with revolutionary libraries in Python Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and more Who This Book Is For This book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired. What You Will Learn Get a practical deep dive into deep learning algorithms Explore deep learning further with Theano, Caffe, Keras, and TensorFlow Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines Dive into Deep Belief Nets and Deep Neural Networks Discover more deep learning algorithms with Dropout and Convolutional Neural Networks Get to know device strategies so you can use deep learning algorithms and libraries in the real world In Detail With an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries. The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results. Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques. Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you'll find everything inside. Style and approach Python Machine Learning by example follows practical hands on approach. It walks you through the key elements of Python and its powerful machine learning libraries with the help of real world projects.
Internet Of Things Smart Spaces And Next Generation Networks And Systems
DOWNLOAD
Author : Olga Galinina
language : en
Publisher: Springer
Release Date : 2016-09-19
Internet Of Things Smart Spaces And Next Generation Networks And Systems written by Olga Galinina and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-19 with Computers categories.
This book constitutes the joint refereed proceedings of the 16th International Conference on Next Generation Wired/Wireless Advanced Networks and Systems, NEW2AN 2016, and the 9th Conference on Internet of Things and Smart Spaces, ruSMART 2016, held in St. Petersburg, Russia, in September 2016. The 69 revised full papers were carefully reviewed and selected from 204 submissions. The 12 papers selected for ruSMART are organized in topical sections on new generation of smart services; smart services serving telecommunication networks; role of context for smart services; and smart services in automotive industry. The 57 papers from NEW2AN deal with the following topics: cooperative communications; wireless networks; wireless sensor networks; security issues; IoT and industrial IoT; NoC and positioning; ITS; network issues; SDN; satellite communications; signals and circuits; advanced materials and their properties; and economics and business.
Data Driven Decision Making For Business
DOWNLOAD
Author : Claus Grand Bang
language : en
Publisher: Taylor & Francis
Release Date : 2024-08-22
Data Driven Decision Making For Business written by Claus Grand Bang and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-22 with Business & Economics categories.
Research shows that companies that employ data-driven decision-making are more productive, have a higher market value, and deliver higher returns for their shareholders. In this book, the reader will discover the history, theory, and practice of data-driven decision-making, learning how organizations and individual managers alike can utilize its methods to avoid cognitive biases and improve confidence in their decisions. It argues that value does not come from data, but from acting on data. Throughout the book, the reader will examine how to convert data to value through data-driven decision-making, as well as how to create a strong foundation for such decision-making within organizations. Covering topics such as strategy, culture, analysis, and ethics, the text uses a collection of diverse and up-to-date case studies to convey insights which can be developed into future action. Simultaneously, the text works to bridge the gap between data specialists and businesspeople. Clear learning outcomes and chapter summaries ensure that key points are highlighted, enabling lecturers to easily align the text to their curriculums. Data-Driven Decision-Making for Business provides important reading for undergraduate and postgraduate students of business and data analytics programs, as well as wider MBA classes. Chapters can also be used on a standalone basis, turning the book into a key reference work for students graduating into practitioners. The book is supported by online resources, including PowerPoint slides for each chapter.
Applied Machine Learning With Mllib
DOWNLOAD
Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-06-03
Applied Machine Learning With Mllib written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-03 with Computers categories.
"Applied Machine Learning with MLlib" Harness the full potential of large-scale machine learning with "Applied Machine Learning with MLlib," a comprehensive guide designed for practitioners and engineers working in modern data environments. This book delves into the architectural pillars of Apache Spark and MLlib, illuminating the principles of distributed computing that enable robust, scalable machine learning solutions in production. Readers will gain a deep understanding of core internals, from resilient distributed datasets and resource management to API evolution and fault-tolerant deployment strategies—empowering them to architect high-performance ML systems across clusters and clouds. Covering the entire machine learning pipeline, the book offers practical guidance on data ingestion, transformation, feature engineering, and both supervised and unsupervised algorithm implementation at scale. In-depth walkthroughs demonstrate best practices for model evaluation, hyperparameter optimization, clustering, and anomaly detection—all tailored for the realities of distributed data. With dedicated chapters on automation, reproducibility, and model management, readers will learn to design robust ML pipelines, custom transformers, and orchestrate reproducible experiments using industry-standard tools. Beyond foundational topics, the book explores advanced capabilities including streaming analytics, online learning, federated privacy-preserving ML, graph-based approaches, and distributed deep learning integrations. Real-world case studies in personalization, NLP, predictive maintenance, fraud detection, and healthcare illustrate end-to-end solutions and organizational best practices. Whether deploying at web scale or tackling sensitive data environments, "Applied Machine Learning with MLlib" equips professionals with practical patterns and expert insights for building, optimizing, and maintaining state-of-the-art ML applications using Spark's powerful ecosystem.
Next Generation Big Data
DOWNLOAD
Author : Butch Quinto
language : en
Publisher: Apress
Release Date : 2018-06-12
Next Generation Big Data written by Butch Quinto and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-12 with Computers categories.
Utilize this practical and easy-to-follow guide to modernize traditional enterprise data warehouse and business intelligence environments with next-generation big data technologies. Next-Generation Big Data takes a holistic approach, covering the most important aspects of modern enterprise big data. The book covers not only the main technology stack but also the next-generation tools and applications used for big data warehousing, data warehouse optimization, real-time and batch data ingestion and processing, real-time data visualization, big data governance, data wrangling, big data cloud deployments, and distributed in-memory big data computing. Finally, the book has an extensive and detailed coverage of big data case studies from Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard. What You’ll Learn Install Apache Kudu, Impala, and Spark to modernize enterprise data warehouse and business intelligence environments, complete with real-world, easy-to-follow examples, and practical advice Integrate HBase, Solr, Oracle, SQL Server, MySQL, Flume, Kafka, HDFS, and Amazon S3 with Apache Kudu, Impala, and Spark Use StreamSets, Talend, Pentaho, and CDAP for real-time and batch data ingestion and processing Utilize Trifacta, Alteryx, and Datameer for data wrangling and interactive data processing Turbocharge Spark with Alluxio, a distributed in-memory storage platform Deploy big data in the cloud using Cloudera Director Perform real-time data visualization and time series analysis using Zoomdata, Apache Kudu, Impala, and Spark Understand enterprise big data topics such as big data governance, metadata management, data lineage, impact analysis, and policy enforcement, and how to use Cloudera Navigator to perform common data governance tasks Implement big data use cases such as big data warehousing, data warehouse optimization, Internet of Things, real-time data ingestion and analytics, complex event processing, and scalable predictive modeling Study real-world big data case studies from innovative companies, including Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard Who This Book Is For BI and big data warehouse professionals interested in gaining practical and real-world insight into next-generation big data processing and analytics using Apache Kudu, Impala, and Spark; and those who want to learn more about other advanced enterprise topics
Artificial Intelligence For Autonomous Networks
DOWNLOAD
Author : Mazin Gilbert
language : en
Publisher: CRC Press
Release Date : 2018-09-25
Artificial Intelligence For Autonomous Networks written by Mazin Gilbert and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-25 with Computers categories.
Artificial Intelligence for Autonomous Networks introduces the autonomous network by juxtaposing two unique technologies and communities: Networking and AI. The book reviews the technologies behind AI and software-defined network/network function virtualization, highlighting the exciting opportunities to integrate those two worlds. Outlining the new frontiers for autonomous networks, this book highlights their impact and benefits to consumers and enterprise customers. It also explores the potential of the autonomous network for transforming network operation, cyber security, enterprise services, 5G and IoT, infrastructure monitoring and traffic optimization, and finally, customer experience and care. With contributions from leading experts, this book will provide an invaluable resource for network engineers, software engineers, artificial intelligence, and machine learning researchers.
Human Centric Integration Of Next Generation Data Science And Blockchain Technology
DOWNLOAD
Author : Amit Kumar Tyagi
language : en
Publisher: Academic Press
Release Date : 2025-03-17
Human Centric Integration Of Next Generation Data Science And Blockchain Technology written by Amit Kumar Tyagi and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-17 with Science categories.
Human- Centric Integration of Next Generation Data Science and Blockchain Technology: Advancing Society 5.0 Paradigms focuses on the current technological landscape, addressing the evolving integration of data science and blockchain within the context of Society 5.0. This comprehensive resource explains the convergences between data science, blockchain, and the human-centric vision of Society 5.0, while also filling the gap in understanding and navigating this transformative intersection with recent shifts towards more decentralized and data-driven paradigms.The book introduces the concept of Society 5.0, examining the historical context, and outlines the evolving technological landscape shaping our interconnected future. It discusses the fundamental principles of data science, from data collection and preprocessing to exploratory data analysis and explains the transformative impact of data science and blockchain across industries such as healthcare, finance, education, and transportation. This book is essential to understanding and shaping the future of technology and society from decentralized solutions to predictive analytics/ emerging technologies. - Addresses the evolving integration of data science and blockchain within the context of Society 5.0 - Introduces the basic architecture and taxonomy of blockchain technology - Explores the future urban lives under the concept of "Society 5.0", characterized by the key phrases of data-driven society and knowledge-intensive society - Offers a firm foundation and understanding of recent advancements in various domains such as data analytics, neural networks, computer vision, and robotics, along with practical solutions to existing problems in fields such as healthcare, manufacturing industries, security, and infrastructure management