Data Science And Network Engineering

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Data Analytics for IT Networks

Author : John Garrett
Publisher : Cisco Press
ISBN 13 : 0135183448
Total Pages : 745 pages
Book Rating : 4.1/5 (351 download)

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Book Synopsis Data Analytics for IT Networks by : John Garrett

Download or read book Data Analytics for IT Networks written by John Garrett and published by Cisco Press. This book was released on 2018-10-24 with total page 745 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use data analytics to drive innovation and value throughout your network infrastructure Network and IT professionals capture immense amounts of data from their networks. Buried in this data are multiple opportunities to solve and avoid problems, strengthen security, and improve network performance. To achieve these goals, IT networking experts need a solid understanding of data science, and data scientists need a firm grasp of modern networking concepts. Data Analytics for IT Networks fills these knowledge gaps, allowing both groups to drive unprecedented value from telemetry, event analytics, network infrastructure metadata, and other network data sources. Drawing on his pioneering experience applying data science to large-scale Cisco networks, John Garrett introduces the specific data science methodologies and algorithms network and IT professionals need, and helps data scientists understand contemporary network technologies, applications, and data sources. After establishing this shared understanding, Garrett shows how to uncover innovative use cases that integrate data science algorithms with network data. He concludes with several hands-on, Python-based case studies reflecting Cisco Customer Experience (CX) engineers’ supporting its largest customers. These are designed to serve as templates for developing custom solutions ranging from advanced troubleshooting to service assurance. Understand the data analytics landscape and its opportunities in Networking See how elements of an analytics solution come together in the practical use cases Explore and access network data sources, and choose the right data for your problem Innovate more successfully by understanding mental models and cognitive biases Walk through common analytics use cases from many industries, and adapt them to your environment Uncover new data science use cases for optimizing large networks Master proven algorithms, models, and methodologies for solving network problems Adapt use cases built with traditional statistical methods Use data science to improve network infrastructure analysisAnalyze control and data planes with greater sophistication Fully leverage your existing Cisco tools to collect, analyze, and visualize data

Data Science and Network Engineering

Author : Suyel Namasudra
Publisher : Springer Nature
ISBN 13 : 9819967554
Total Pages : 525 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Data Science and Network Engineering by : Suyel Namasudra

Download or read book Data Science and Network Engineering written by Suyel Namasudra and published by Springer Nature. This book was released on 2023-11-02 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Network Models for Data Science

Author : Alan Julian Izenman
Publisher : Cambridge University Press
ISBN 13 : 1108835767
Total Pages : 501 pages
Book Rating : 4.1/5 (88 download)

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Book Synopsis Network Models for Data Science by : Alan Julian Izenman

Download or read book Network Models for Data Science written by Alan Julian Izenman and published by Cambridge University Press. This book was released on 2022-12-31 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to describe modern methods for analyzing complex networks arising from a wide range of disciplines.

Data-Driven Science and Engineering

Author : Steven L. Brunton
Publisher : Cambridge University Press
ISBN 13 : 1009098489
Total Pages : 615 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Data-Driven Science and Engineering by : Steven L. Brunton

Download or read book Data-Driven Science and Engineering written by Steven L. Brunton and published by Cambridge University Press. This book was released on 2022-05-05 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Neural Networks for Applied Sciences and Engineering

Author : Sandhya Samarasinghe
Publisher : CRC Press
ISBN 13 : 1420013068
Total Pages : 596 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Neural Networks for Applied Sciences and Engineering by : Sandhya Samarasinghe

Download or read book Neural Networks for Applied Sciences and Engineering written by Sandhya Samarasinghe and published by CRC Press. This book was released on 2016-04-19 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: In response to the exponentially increasing need to analyze vast amounts of data, Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition provides scientists with a simple but systematic introduction to neural networks. Beginning with an introductory discussion on the role of neural networks in

An Engineering Approach to Computer Networking

Author : Srinivasan Keshav
Publisher : Addison-Wesley Professional
ISBN 13 :
Total Pages : 702 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis An Engineering Approach to Computer Networking by : Srinivasan Keshav

Download or read book An Engineering Approach to Computer Networking written by Srinivasan Keshav and published by Addison-Wesley Professional. This book was released on 1997 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: Taking a unique "engineering" approach that will help readers gain a grasp of not just how but also why networks work the way they do, this book includes the very latest network technology--including the first practical treatment of Asynchronous Transfer Mode (ATM). The CD-ROM contains an invaluable network simulator.

A First Course in Network Science

Author : Filippo Menczer
Publisher : Cambridge University Press
ISBN 13 : 1108579612
Total Pages : 275 pages
Book Rating : 4.1/5 (85 download)

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Book Synopsis A First Course in Network Science by : Filippo Menczer

Download or read book A First Course in Network Science written by Filippo Menczer and published by Cambridge University Press. This book was released on 2020-01-30 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networks are everywhere: networks of friends, transportation networks and the Web. Neurons in our brains and proteins within our bodies form networks that determine our intelligence and survival. This modern, accessible textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Students will develop important, practical skills and learn to write code for using networks in their areas of interest - even as they are just learning to program with Python. Extensive sets of tutorials and homework problems provide plenty of hands-on practice and longer programming tutorials online further enhance students' programming skills. This intuitive and direct approach makes the book ideal for a first course, aimed at a wide audience without a strong background in mathematics or computing but with a desire to learn the fundamentals and applications of network science.

Foundations of Data Science

Author : Avrim Blum
Publisher : Cambridge University Press
ISBN 13 : 1108617360
Total Pages : 433 pages
Book Rating : 4.1/5 (86 download)

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Book Synopsis Foundations of Data Science by : Avrim Blum

Download or read book Foundations of Data Science written by Avrim Blum and published by Cambridge University Press. This book was released on 2020-01-23 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.

Quantum State Transfer and Network Engineering

Author : Georgios M. Nikolopoulos
Publisher : Springer Science & Business Media
ISBN 13 : 3642399371
Total Pages : 258 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Quantum State Transfer and Network Engineering by : Georgios M. Nikolopoulos

Download or read book Quantum State Transfer and Network Engineering written by Georgios M. Nikolopoulos and published by Springer Science & Business Media. This book was released on 2013-10-05 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Faithful communication is a necessary precondition for large-scale quantum information processing and networking, irrespective of the physical platform. Thus, the problems of quantum-state transfer and quantum-network engineering have attracted enormous interest over the last years, and constitute one of the most active areas of research in quantum information processing. The present volume introduces the reader to fundamental concepts and various aspects of this exciting research area, including links to other related areas and problems. The implementation of state-transfer schemes and the engineering of quantum networks are discussed in the framework of various quantum optical and condensed matter systems, emphasizing the interdisciplinary character of the research area. Each chapter is a review of theoretical or experimental achievements on a particular topic, written by leading scientists in the field. The volume aims at both newcomers as well as experienced researchers.

Artificial Intelligence and Data Science Engineering

Author : Dr.Ravi Kumar Saidala
Publisher : Leilani Katie Publication
ISBN 13 : 936348419X
Total Pages : 185 pages
Book Rating : 4.3/5 (634 download)

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Book Synopsis Artificial Intelligence and Data Science Engineering by : Dr.Ravi Kumar Saidala

Download or read book Artificial Intelligence and Data Science Engineering written by Dr.Ravi Kumar Saidala and published by Leilani Katie Publication. This book was released on 2024-07-13 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dr.Ravi Kumar Saidala, Associate Professor, Department of Computer Science and Engineering (Data Science), CMR University, Bangalore, Karnataka, India. Dr.D.Usha Rani, Associate Professor, Department of Computer Science and Applications, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India. Ms.Indu.B, Assistant Professor, Department of Computer Science Engineering, Dayananda Sagar Academy of Technology and Management (DSATM), Bangalore, Karnataka, India. Dr.Shanthala.P.T, Assistant Professor, Department of Computer Science Engineering, PES University, Bangalore, Karnataka, India.

Encyclopedia of Data Science and Machine Learning

Author : Wang, John
Publisher : IGI Global
ISBN 13 : 1799892212
Total Pages : 3296 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Encyclopedia of Data Science and Machine Learning by : Wang, John

Download or read book Encyclopedia of Data Science and Machine Learning written by Wang, John and published by IGI Global. This book was released on 2023-01-20 with total page 3296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.

Cisco CCNA Routing and Switching 200-120 Official Cert Guide Library

Author : Wendell Odom
Publisher : Pearson Education
ISBN 13 : 1587143879
Total Pages : 1111 pages
Book Rating : 4.5/5 (871 download)

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Book Synopsis Cisco CCNA Routing and Switching 200-120 Official Cert Guide Library by : Wendell Odom

Download or read book Cisco CCNA Routing and Switching 200-120 Official Cert Guide Library written by Wendell Odom and published by Pearson Education. This book was released on 2013 with total page 1111 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cisco Press is the official publisher for the New CCENT & CCNA Routing and Switching Certifications. The New Edition of the Best-Selling two-book value priced CCNA Official Cert Guide Library includes Updated Content, New Exercises, 8 Practice Exams, and 150 Minutes of Video Training -- PLUS the CCENT and CCNA Network Simulator Lite Editions with 26 Free Network Simulator Labs. CCNA 200-120 Official Cert Guide Library is a comprehensive review and package for the latest CCNA exams. The two books contained in this package, CCENT / CCNA ICND1 100-101 Official Cert Guide and CCNA ICND2 200-101 Official Cert Guide, present complete reviews and a more challenging and realistic preparation experience. The books have been fully updated to refresh the content for the latest CCNA exam topics and enhance certain key topics that are critical for exam success. Best-selling author and expert instructor Wendell Odom shares preparation hints and test-taking tips, helping you identify areas of weakness and improve both your conceptual knowledge and hands-on skills. These official study guides help you master all the topics on the CCNA exams, including: Networking fundamentals Ethernet LANs and switches IPv4 addressing and subnetting Operating Cisco routers Configuring OSPF ACLs and NAT IPv6 fundamentals, implementation, and troubleshooting LAN switching IPv4 routing VPNs OSPF and EIGRP configuration and troubleshooting Wide area networks and Frame Relay Network management Well regarded for its level of detail, study plans, assessment features, challenging review questions and exercises, video instruction, and hands-on labs, these official study guides help you master the concepts and techniques that ensure your exam success. CCNA 200-120 Official Cert Guide Library is part of a recommended learning path from Cisco that includes simulation and hands-on training from authorized Cisco Learning Partners and self-study products from Cisco Press. 1587143879 / 9781587143878 CCNA Routing and Switching 200-120 Official Cert Guide Library 1/e Package consists of: 0131357549 / 9780131357549 TWO INCH MYLAR CLEAR WAFER SEAL 0133372006 / 9780133372007 Empty Slipcase for Exam 29 Cert Library 1587143739 / 9781587143731 CCNA Routing and Switching ICND2 200-101 Official Cert Guide 1587143852 / 9781587143854 CCENT/CCNA ICND1 100-101 Official Cert Guide

Statistical Analysis of Network Data

Author : Eric D. Kolaczyk
Publisher : Springer Science & Business Media
ISBN 13 : 0387881468
Total Pages : 397 pages
Book Rating : 4.3/5 (878 download)

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Book Synopsis Statistical Analysis of Network Data by : Eric D. Kolaczyk

Download or read book Statistical Analysis of Network Data written by Eric D. Kolaczyk and published by Springer Science & Business Media. This book was released on 2009-04-20 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.

Hadoop in Practice

Author : Alex Holmes
Publisher : Manning Publications
ISBN 13 : 9781617292224
Total Pages : 512 pages
Book Rating : 4.2/5 (922 download)

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Book Synopsis Hadoop in Practice by : Alex Holmes

Download or read book Hadoop in Practice written by Alex Holmes and published by Manning Publications. This book was released on 2014-10-12 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Hadoop in Practice, Second Edition provides over 100 tested, instantly useful techniques that will help you conquer big data, using Hadoop. This revised new edition covers changes and new features in the Hadoop core architecture, including MapReduce 2. Brand new chapters cover YARN and integrating Kafka, Impala, and Spark SQL with Hadoop. You'll also get new and updated techniques for Flume, Sqoop, and Mahout, all of which have seen major new versions recently. In short, this is the most practical, up-to-date coverage of Hadoop available anywhere. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book It's always a good time to upgrade your Hadoop skills! Hadoop in Practice, Second Edition provides a collection of 104 tested, instantly useful techniques for analyzing real-time streams, moving data securely, machine learning, managing large-scale clusters, and taming big data using Hadoop. This completely revised edition covers changes and new features in Hadoop core, including MapReduce 2 and YARN. You'll pick up hands-on best practices for integrating Spark, Kafka, and Impala with Hadoop, and get new and updated techniques for the latest versions of Flume, Sqoop, and Mahout. In short, this is the most practical, up-to-date coverage of Hadoop available. Readers need to know a programming language like Java and have basic familiarity with Hadoop. What's Inside Thoroughly updated for Hadoop 2 How to write YARN applications Integrate real-time technologies like Storm, Impala, and Spark Predictive analytics using Mahout and RR Readers need to know a programming language like Java and have basic familiarity with Hadoop. About the Author Alex Holmes works on tough big-data problems. He is a software engineer, author, speaker, and blogger specializing in large-scale Hadoop projects. Table of Contents PART 1 BACKGROUND AND FUNDAMENTALS Hadoop in a heartbeat Introduction to YARN PART 2 DATA LOGISTICS Data serialization—working with text and beyond Organizing and optimizing data in HDFS Moving data into and out of Hadoop PART 3 BIG DATA PATTERNS Applying MapReduce patterns to big data Utilizing data structures and algorithms at scale Tuning, debugging, and testing PART 4 BEYOND MAPREDUCE SQL on Hadoop Writing a YARN application

Data Science Techniques for Beginner Network Administrators

Author : Yulius Yus
Publisher : AMERTA MEDIA
ISBN 13 : 6234196721
Total Pages : 122 pages
Book Rating : 4.2/5 (341 download)

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Book Synopsis Data Science Techniques for Beginner Network Administrators by : Yulius Yus

Download or read book Data Science Techniques for Beginner Network Administrators written by Yulius Yus and published by AMERTA MEDIA. This book was released on 2024-08-12 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is an old saying: "It is easier to wake someone who is sound asleep than to wake who is pretending to sleep." As network administrators, competing with Al systems in the future is not an impossibility. Analyzing events with simple examples like comparing bandwidth, throughput, jitter, and optimizing server resource usage can be exhausting when applied to dozens or hundreds of devices. For instance, how do we classify when the bandwidth is low in one place but normal elsewhere based on several sample events? Or how do we classify which servers need maintenance and which do not, based on existing data parameters, referring to unsupervised and supervised learning? Classification models can indeed simplify and optimize our work, saving time compared to performing network maintenance one by one, using only Google Colab. In this context, we have tried using a small of unsupervised and supervised learning to process data from simple network case studies. These data are analyzed for classification, regression, and prediction using Python scripts implemented in Google Colab. This book serves as a starting point to be developed into a continuous series, extending to supervised learning, deep learning, and reinforcement learning, which are still in the testing and writing phase. We hope this new approach benefits network administrators wherever you are.

Statistical Analysis of Network Data with R

Author : Eric D. Kolaczyk
Publisher : Springer
ISBN 13 : 1493909835
Total Pages : 214 pages
Book Rating : 4.4/5 (939 download)

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Book Synopsis Statistical Analysis of Network Data with R by : Eric D. Kolaczyk

Download or read book Statistical Analysis of Network Data with R written by Eric D. Kolaczyk and published by Springer. This book was released on 2014-05-22 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).

Data Science from Scratch

Author : Joel Grus
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491904399
Total Pages : 336 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Data Science from Scratch by : Joel Grus

Download or read book Data Science from Scratch written by Joel Grus and published by "O'Reilly Media, Inc.". This book was released on 2015-04-14 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases