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Big Data with Hadoop MapReduce
The authors provide an understanding of big data and MapReduce by clearly presenting the basic terminologies and concepts. They have employed over 100 illustrations and many worked-out examples to convey the concepts and methods used in big data, the inner workings of MapReduce, and single node/multi-node installation on physical/virtual machines. This book covers almost all the necessary information on Hadoop MapReduce for most online certification exams. Upon completing this book, readers will find it easy to understand other big data processing tools such as Spark, Storm, etc. Ultimately, readers will be able to: • understand what big data is and the factors that are involved • understand the inner workings of MapReduce, which is essential for certification exams • learn the features and weaknesses of MapReduce • set up Hadoop clusters with 100s of physical/virtual machines • create a virtual machine in AWS • write MapReduce with Eclipse in a simple way • understand other big data processing tools and their applications
Data Science and Network Engineering
This book includes research papers presented at the International Conference on Data Science and Network Engineering (ICDSNE 2023) organized by the Department of Computer Science and Engineering, National Institute of Technology Agartala, Tripura, India, during July 21–22, 2023. It includes research works from researchers, academicians, business executives, and industry professionals for solving real-life problems by using the advancements and applications of data science and network engineering. This book covers many advanced topics, such as artificial intelligence (AI), machine learning (ML), deep learning (DL), computer networks, blockchain, security and privacy, Internet of things (IoT), cloud computing, big data, supply chain management, and many more. Different sections of this book are highly beneficial for the researchers, who are working in the field of data science and network engineering.
Machine Learning and Knowledge Discovery in Databases
Chapters “On the Current State of Reproducibility and Reporting of Uncertainty for Aspect-Based SentimentAnalysis” and “Contextualized Graph Embeddings for Adverse Drug Event Detection” are licensed under theterms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). For further details see license information in the chapter.
Soft Computing and Its Engineering Applications
This book constitutes the refereed proceedings of the 4th International Conference on Soft Computing and its Engineering Applications, icSoftComp 2022, held in Changa, Anand, India during December 9–10, 2022. The 33 full papers and 3 short papers included in this book were carefully reviewed and selected from 342 submissions. They were organized in topical sections as follows: Theory and Methods; Systems and Applications; and Hybrid Techniques.
Data Mining
This book constitutes the refereed proceedings of the 19th Australasian Conference on Data Mining, AusDM 2021, held in Brisbane, Queensland, Australia, in December 2021.* The 16 revised full papers presented were carefully reviewed and selected from 32 submissions. The papers are organized in sections on research track and application track. *Due to the COVID-19 pandemic the conference was held online.
Big Data Applications in Industry 4.0
Industry 4.0 is the latest technological innovation in manufacturing with the goal to increase productivity in a flexible and efficient manner. Changing the way in which manufacturers operate, this revolutionary transformation is powered by various technology advances including Big Data analytics, Internet of Things (IoT), Artificial Intelligence (AI), and cloud computing. Big Data analytics has been identified as one of the significant components of Industry 4.0, as it provides valuable insights for smart factory management. Big Data and Industry 4.0 have the potential to reduce resource consumption and optimize processes, thereby playing a key role in achieving sustainable development. Big...
Building Arduino Projects for the Internet of Things
Gain a strong foundation of Arduino-based device development, from which you can go in any direction according to your specific development needs and desires. You'll build Arduino-powered devices for everyday use, and then connect those devices to the Internet. You'll be introduced to the building blocks of IoT, and then deploy those principles to by building a variety of useful projects. Projects in the books gradually introduce the reader to key topics such as internet connectivity with Arduino, common IoT protocols, custom web visualization, and Android apps that receive sensor data on-demand and in realtime. IoT device enthusiasts of all ages will want this book by their side when develo...
Spark for Python Developers
A concise guide to implementing Spark Big Data analytics for Python developers, and building a real-time and insightful trend tracker data intensive appAbout This Book• Set up real-time streaming and batch data intensive infrastructure using Spark and Python• Deliver insightful visualizations in a web app using Spark (PySpark)• Inject live data using Spark Streaming with real-time eventsWho This Book Is ForThis book is for data scientists and software developers with a focus on Python who want to work with the Spark engine, and it will also benefit Enterprise Architects. All you need to have is a good background of Python and an inclination to work with Spark.What You Will Learn• Cre...
