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Data Center Linux Essentials (Engineering Fully Automated Data Centers) by Jamil Brown
English | December 20, 2024 | ISBN: N/A | ASIN: B0DR5JY5NT | 804 pages | EPUB | 0.68 Mb
Data Center Linux Essentials offers a comprehensive guide to mastering the Linux environment for data center operations. This book covers foundational concepts and advanced techniques crucial for Linux server administration. It starts with understanding the Linux file system hierarchy, managing user accounts, and configuring file permissions, before diving into more specialized topics such as disk partitioning, RAID management, and logical volume management (LVM).

The guide also provides practical instructions for managing system resources using tools like top, htop, and atop, monitoring network performance with utilities such as ping, netstat, and ss, and securing remote connections using ssh with key authentication. Additionally, the book addresses essential system administration tasks, including configuring and managing network interfaces, firewall management with iptables, automating backups with rsync and cron, and ensuring system integrity with tools like strace and sysctl.
Further, the book explores advanced topics such as containerization with Docker, virtualization with KVM, system recovery techniques, and disaster recovery strategies. It also highlights the importance of security, providing insights into hardening Linux servers, configuring SSL/TLS certificates, and using AppArmor for enhanced protection. With practical examples, this resource equips system administrators with the skills necessary to efficiently manage and secure Linux servers in modern data center environments.

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Data Center Operations Training Mastery Course: Book 1 (Engineering Fully Automated Data Centers) by Jamil Brown
English | December 16, 2024 | ISBN: N/A | ASIN: B0DH587JK1 | 670 pages | EPUB | 1.43 Mb
Data Center Operations Training Mastery Course: Book 1

This comprehensive guide is an all-in-one resource for understanding and excelling in data center operations. Covering critical topics such as networking infrastructure, fiber optic and copper cabling, optical connectors like MTP/MPO, and advanced networking protocols (DWDM, CWDM, BGP, DHCP, DNS), it equips readers with deep insights into modern data center technologies. The book delves into server hardware components-CPUs, RAM, RAID systems, GPUs, PSUs, and thermal management-while offering hands-on guidance for software tools like IPMI Tool, Dell iDRAC, and BMC suites. With detailed sections on RAID troubleshooting, hardware maintenance, and logical roles like NOCs and cloud networking engineering, this guide bridges the gap between physical hardware knowledge and cloud operations expertise. Designed to train beginners and professionals alike, it serves as the ultimate blueprint for launching a successful career in data centers.

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Data Center Operations Training Mastery Course (Engineering Fully Automated Data Centers) by Jamil Brown
English | December 18, 2024 | ISBN: N/A | ASIN: B0DQXL2Q7C | 681 pages | EPUB | 1.16 Mb
Data Center Operations Training Mastery Course

Mastering Data Center Operations is the definitive resource for individuals seeking careers as data center hardware technicians, network engineers, or cloud operations specialists. The book thoroughly explores essential topics like network cabling (fiber optic and copper), hardware diagnostics with Fluke Network kits, and advanced routing protocols such as OSPF and BGP. Readers gain in-depth knowledge of RAID systems, hard drives (SSD, NVMe, HDD), and hardware components-motherboards, CPUs, and thermal systems-alongside critical server software like Linux and Windows Server troubleshooting. Practical guidance on managing cloud networking infrastructure, network switches (Cisco, Arista, Juniper), and data center redundancy strategies ensures readers are prepared for real-world challenges. Whether starting in hardware maintenance or advancing to logical support roles, this book provides the skills, tools, and industry insights needed to excel in modern data centers.

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Data Center Operations Training Mastery Course (Engineering Fully Automated Data Centers) by Jamil Brown
English | December 20, 2024 | ISBN: N/A | ASIN: B0DR5WK4JS | 714 pages | EPUB | 1.54 Mb
Data Center Operations Training Mastery Course - Server and Network Hardware Troubleshooting

This comprehensive guide delves deep into the essential skills required for troubleshooting server and network hardware issues in data center environments.
In the server hardware section, readers will explore a wide range of issues, from server boot failures to overheating problems, as well as solutions for RAID array failures, faulty power supplies, and memory-related errors. Key areas of focus include repairing storage devices, handling CPU failures, and managing server firmware and BIOS issues. Additionally, this book covers practical scenarios such as addressing server downtime, data corruption, and performance degradation, as well as offering strategies for effective server maintenance and hardware replacement.
The network hardware troubleshooting section extends to the complexities of diagnosing and fixing connectivity issues, including network switch failures, cable faults, and VLAN misconfigurations. The book also discusses key concepts like network redundancy, IP address conflicts, and bandwidth bottlenecks, along with the troubleshooting of routing problems, fiber optic issues, and network protocol conflicts.
By the end of this training, readers will be well-versed in solving critical server and network issues, enhancing their ability to maintain a stable and efficient data center environment.

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Data Center Operations Training Mastery Course (Engineering Fully Automated Data Centers) by Jamil Brown
English | December 20, 2024 | ISBN: N/A | ASIN: B0DR48G57W | 795 pages | EPUB | 1.24 Mb
Data Center Operations Training Mastery Course: Book 4 - Server and Remote Management Solutions

This comprehensive guide delves into the critical components of remote server management through tools like IPMI (Intelligent Platform Management Interface), ILO (Integrated Lights-Out), IDRAC (Integrated Dell Remote Access Controller), and BMC (Baseboard Management Controller). These technologies are essential for effective server operations, allowing IT professionals to monitor, manage, and troubleshoot server hardware from any location, ensuring optimal uptime and performance.
Book 4 focuses on how these interfaces and controllers function to provide remote power management, hardware health monitoring, and diagnostics. The book covers vital topics such as configuring and managing system event logs (SEL), performing remote reboots, and utilizing virtual media for remote OS installation and recovery. It also emphasizes the importance of securing remote access through best practices like SSL encryption and multi-factor authentication.
Throughout the course, readers are introduced to advanced configurations like RAID management, server BIOS updates, and the integration of these management tools with centralized monitoring systems. The guide offers detailed steps for configuring alerts for hardware failures, automating server health checks, and troubleshooting common issues, ensuring that data center professionals are equipped with the knowledge to maintain and repair servers remotely and efficiently. Whether dealing with power failures, hardware faults, or firmware updates, this training provides the expertise needed to tackle any challenge in modern data center environments.

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Kukatlapalli Pradeep Kumar, "Data Engineering and Data Science: Concepts and Applications"
English | ISBN: 1119841879 | 2023 | 464 pages | PDF | 114 MB
DATA ENGINEERING and DATA SCIENCE

Written and edited by one of the most prolific and well-known experts in the field and his team, this exciting new volume is the "one-stop shop" for the concepts and applications of data science and engineering for data scientists across many industries.
The field of data science is incredibly broad, encompassing everything from cleaning data to deploying predictive models. However, it is rare for any single data scientist to be working across the spectrum day to day. Data scientists usually focus on a few areas and are complemented by a team of other scientists and analysts. Data engineering is also a broad field, but any individual data engineer doesn't need to know the whole spectrum of skills. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information.
Read more

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Data Exfiltration Threats and Prevention Techniques: Machine Learning and Memory-Based Data Security by Zahir Tari, Nasrin Sohrabi, Yasaman Samadi
English | June 7, 2023 | ISBN: 1119898870 | 288 pages | MOBI | 11 Mb
DATA EXFILTRATION THREATS AND PREVENTION TECHNIQUES

Comprehensive resource covering threat prevention techniques for data exfiltration and applying machine learning applications to aid in identification and prevention
Data Exfiltration Threats and Prevention Techniques provides readers the knowledge needed to prevent and protect from malware attacks by introducing existing and recently developed methods in malware protection using AI, memory forensic, and pattern matching, presenting various data exfiltration attack vectors and advanced memory-based data leakage detection, and discussing ways in which machine learning methods have a positive impact on malware detection.
Providing detailed descriptions of the recent advances in data exfiltration detection methods and technologies, the authors also discuss details of data breach countermeasures and attack scenarios to show how the reader may identify a potential cyber attack in the real world.
Composed of eight chapters, this book presents a better understanding of the core issues related to the cyber-attacks as well as the recent methods that have been developed in the field.
In Data Exfiltration Threats and Prevention Techniques, readers can expect to find detailed information on:Sensitive data classification, covering text pre-processing, supervised text classification, automated text clustering, and other sensitive text detection approachesSupervised machine learning technologies for intrusion detection systems, covering taxonomy and benchmarking of supervised machine learning techniquesBehavior-based malware detection using API-call sequences, covering API-call extraction techniques and detecting data stealing behavior based on API-call sequencesMemory-based sensitive data monitoring for real-time data exfiltration detection and advanced time delay data exfiltration attack and detectionAimed at professionals and students alike, Data Exfiltration Threats and Prevention Techniques highlights a range of machine learning methods that can be used to detect potential data theft and identifies research gaps and the potential to make change in the future as technology continues to grow.

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Data Fusion Mathematics
by Raol, Jitendra R.;Selvi, S. Sethu;Kashyap, Sudesh K.;Sanketh, Ailneni;, Sethu Selvi, S., Kashyap, Sudesh K., Sanketh, Ailneni
English | 2025 | ISBN: 1032904364 | 630 pages | True EPUB | 16.27 MB

Data Fusion Mathematics: Theory and Practice offers a comprehensive overview of data fusion (DF) and provides a proper and adequate understanding of the basic mathematics directly related to DF. This new edition offers updated chapters alongside four new chapters that are based on recent research carried out by the authors, including topics on machine learning techniques, target localization using a network of 2D ground radar, thermal imaging sensors for multi‑target angle‑only tracking, and multi‑sensor data fusion for a single platform and team platforms. This book also covers major mathematical expressions, formulae and equations, and, where feasible, their derivations. It discusses signed distance function concepts, DF models and architectures, aspects and methods of types 1 and 2 fuzzy logics, and related practical applications. In addition, the authors cover soft computing paradigms that are finding increasing applications in multi-sensory DF approaches and applications. This text is geared toward researchers, scientists, teachers, and practicing engineers interested in and working in the multi‑sensor data fusion area.

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Data Science and Applications: Proceedings of ICDSA 2024, Volume 5
English | 2025 | ISBN: 9819611849 | 532 Pages | PDF (True) | 32 MB
This book gathers outstanding papers presented at the 5th International Conference on Data Science and Applications (ICDSA 2024), organized by Soft Computing Research Society (SCRS) and Malaviya National Institute of Technology Jaipur, India, from 17 to 19 July 2024. The book is divided into four volumes, and it covers theoretical and empirical developments in various areas of big data analytics, big data technologies, decision tree learning, wireless communication, wireless sensor networking, bioinformatics and systems, artificial neural networks, deep learning, genetic algorithms, data mining, fuzzy logic, optimization algorithms, image processing, computational intelligence in civil engineering, and creative computing.

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Data Science and Big Data Analytics: Proceedings of IDBA 2024
English | 2025 | ISBN: 981979854X | 1328 Pages | PDF EPUB (True) | 132 MB
This book features high-quality research papers presented at the Fourth International Conference on Data Science and Big Data Analytics (IDBA 2024), organized by Symbiosis University of Applied Sciences, Indore, India, in association with ACM and IEEE Computer Society in hybrid mode during July 12-13, 2024. This book discusses the topics such as data science, artificial intelligence, machine learning, quantum computing, big data and cloud security, computation security, big data security, information security, forecasting, data analytics, mathematics for data science, graph theory and application in data science, data visualization, computer vision, and analytics for social networks.

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Data Science with Semantic Technologies: Theory, Practice and Application (Advances in Intelligent and Scientific Computing) by Archana Patel, Narayan C. Debnath, Bharat Bhusan
English | September 14, 2022 | ISBN: 1119864984 | 464 pages | MOBI | 10 Mb
DATA SCIENCE WITH SEMANTIC TECHNOLOGIES

This book will serve as an important guide toward applications of data science with semantic technologies for the upcoming generation and thus becomes a unique resource for scholars, researchers, professionals, and practitioners in this field.
To create intelligence in data science, it becomes necessary to utilize semantic technologies which allow machine-readable representation of data. This intelligence uniquely identifies and connects data with common business terms, and it also enables users to communicate with data. Instead of structuring the data, semantic technologies help users to understand the meaning of the data by using the concepts of semantics, ontology, OWL, linked data, and knowledge-graphs. These technologies help organizations to understand all the stored data, adding the value in it, and enabling insights that were not available before. As data is the most important asset for any organization, it is essential to apply semantic technologies in data science to fulfill the need of any organization.
Data Science with Semantic Technologies provides a roadmap for the deployment of semantic technologies in the field of data science. Moreover, it highlights how data science enables the user to create intelligence through these technologies by exploring the opportunities and eradicating the challenges in the current and future time frame. In addition, this book provides answers to various questions like: Can semantic technologies be able to facilitate data science? Which type of data science problems can be tackled by semantic technologies? How can data scientists benefit from these technologies? What is knowledge data science? How does knowledge data science relate to other domains? What is the role of semantic technologies in data science? What is the current progress and future of data science with semantic technologies? Which types of problems require the immediate attention of researchers?
Audience
Researchers in the fields of data science, semantic technologies, artificial intelligence, big data, and other related domains, as well as industry professionals, software engineers/scientists, and project managers who are developing the software for data science. Students across the globe will get the basic and advanced knowledge on the current state and potential future of data science.

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Data Without Labels
by Vaibhav Verdhan
English | 2025 | ISBN:1617298727 | 354 pages | True PDF | 38.83 MB

Discover all-practical implementations of the key algorithms and models for handling unlabelled data. Full of case studies demonstrating how to apply each technique to real-world problems.
In Data Without Labels you'll learn:
Fundamental building blocks and concepts of machine learning and unsupervised learning
Data cleaning for structured and unstructured data like text and images
Clustering algorithms like kmeans, hierarchical clustering, DBSCAN, Gaussian Mixture Models, and Spectral clustering
Dimensionality reduction methods like Principal Component Analysis (PCA), SVD, Multidimensional scaling, and t-SNE
Association rule algorithms like aPriori, ECLAT, SPADE
Unsupervised time series clustering, Gaussian Mixture models, and statistical methods
Building neural networks such as GANs and autoencoders
Dimensionality reduction methods like Principal Component Analysis and multidimensional scaling
Association rule algorithms like aPriori, ECLAT, and SPADE
Working with Python tools and libraries like sklearn, bumpy, Pandas, matDescriptionlib, Seaborn, Keras, TensorFlow, andFflask
How to interpret the results of unsupervised learning
Choosing the right algorithm for your problem
Deploying unsupervised learning to production
Data Without Labels introduces mathematical techniques, key algorithms, and Python implementations that will help you build machine learning models for unannotated data. You'll discover hands-off and unsupervised machine learning approaches that can still untangle raw, real-world datasets and support sound strategic decisions for your business.
Don't get bogged down in theory-the book bridges the gap between complex math and practical Python implementations, covering end-to-end model development all the way through to production deployment. You'll discover the business use cases for machine learning and unsupervised learning, and access insightful research papers to complete your knowledge.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the technology
Unsupervised learning and machine learning algorithms draw inferences from unannotated data sets. The self-organizing approach to machine learning is great for spotting patterns a human might miss.
About the book
Data Without Labels teaches you to apply a full spectrum of machine learning algorithms to raw data. You'll master everything from kmeans and hierarchical clustering, to advanced neural networks like GANs and Restricted Boltzmann Machines. You'll learn the business use case for different models, and master best practices for structured, text, and image data. Each new algorithm is introduced with a case study for retail, aviation, banking, and more-and you'll develop a Python solution to fix each of these real-world problems. At the end of each chapter, you'll find quizzes, practice datasets, and links to research papers to help you lock in what you've learned and expand your knowledge.
About the reader
For developers and data scientists. Basic Python experience required.
About the author
Vaibhav Verdhan is a seasoned data science professional with rich experience across geographies and domains. He has led multiple engagements in machine learning and artificial intelligence. A leading industry expert, Vaibhav is a regular speaker at conferences and meet-ups and mentors students and professionals. Currently he resides in Ireland where he works as a principal data scientist.

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Data-Driven, Nonparametric, Adaptive Control Theory
English | 2025 | ISBN: 3031780027 | 346 Pages | PDF EPUB (True) | 51 MB
Data-Driven, Nonparametric, Adaptive Control Theory introduces a novel approach to the control of deterministic, nonlinear ordinary differential equations affected by uncertainties. The methods proposed enforce satisfactory trajectory tracking despite functional uncertainties in the plant model. The book employs the properties of reproducing kernel Hilbert (native) spaces to characterize both the functional space of uncertainties and the controller's performance. Classical control systems are extended to broader classes of problems and more informative characterizations of the controllers' performances are attained.

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Databases for Data-Centric Geotechnics: Site Characterization (Challenges in Geotechnical and Rock Engineering) by Kok-Kwang Phoon, Chong Tang
English | December 20, 2024 | ISBN: 1032578955 | 490 pages | MOBI | 26 Mb
Databases for Data-Centric Geotechnics forms a definitive reference and guide to databases in geotechnical and rock engineering, to enhance decision-making in geotechnical practice using data-driven methods. This first volume pertains to site characterization. The opening chapter presents an in-depth analysis of site data attributes, including the establishment of a new taxonomy of site data under "4S" (site generalizations, spatial features, sampling characteristics, and smart data) to provide a novel agenda for data-driven site characterization. Type 3 machine learning methods (disruptive value) are possible as sensors become more pervasive and more intelligent. A comprehensive overview of site characterization information is also presented with a focus on its availability, coverage, value to decision making, and challenges. The remaining 13 chapters cover databases of soil and rock properties and the application of these databases to rock socket behavior, rock classification, settlement on soft marine clays, permeability of fine-grained soils, and liquefaction among others. The databases were compiled from studies undertaken in many countries including Austria, Australia, Brazil, Canada, China, France, Finland, Germany, India, Iran, Japan, Korea, Malaysia, Mexico, New Zealand, Norway, Singapore, Sweden, Thailand, the United Kingdom, and the United States.

This volume on site characterization is a companion to the volume on geotechnical structures. Databases for Data-Centric Geotechnics represents the most diverse and comprehensive assembly of database research in a single publication (consisting of two volumes) to date. It follows from Model Uncertainties for Foundation Design, also published by CRC Press, and suits specialist geotechnical engineers, researchers and graduate students.

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Datenschutz und IT-Compliance
German | 2024 | ISBN: 3836286742 | 400 pages | MOBI | 7.99 Mb
Pflichtlektüre für alle IT-Verantwortlichen

IT-Administratoren bewegen Sich bei ihrer täglichen Arbeit regelmäßig in einem juristischen Minenfeld. Welche Daten müssen im Rahmen eines Auskunftsbegehrens herausgegeben werden? Welche Daten gehören in Backups und Logfiles und wann müssen diese gelösscht werden? Was ist beim Betrieb von Websites zu beachten und bei der Datenverarbeitung in der Cloud? Wann drohen Bußgelder? Wer hat warum welche Berechtigungen wofür?
Nur wenige Systemadministratoren oder Compliance-Beauftragte können belastbare Antworten darauf geben. Mit unserem Leitfaden erhalten Sie Grundlagenwissen, Entscheidungshilfen und Praxishinweise an die Hand.
Grundlagen, die Sie kennen sollten
Alles, was Sie über Datenschutz wissen müssen: Grundsätze und Prinzipien, Anforderungen der Datenschutz-Grundverordnung (DSGVO) an den IT-Betrieb, die IT-Sicherheit und an die Administration von Websites.
Wie Sie richtig mit Daten umgehen
Lernen Sie, wie Sie Datenschutzverpflichtungen als Unternehmen umsetzen, mit Datenschutzvorfällen umgehen, Daten richtig exportieren und die von Mitarbeiter*innen korrekt handhaben.
Compliance, Sanktionen, Haftung
Erfahren Sie, was sich eigentlich hinter Compliance verbirgt, und wie Sie sich im Vorfeld gegen Compliance-Verletzungen schützen. Außerdem: Welche Sanktionen haben Sie bei Datenschutzvergehen als IT-Admin zu befürchten?
Aus dem Inhalt
Was sind personenbezogene Daten?
Grundsätze der Datenverarbeitung und des technischen Datenschutz
Systemprotokolle, Weblogs, Backups, Archivierung
Löschpflichten und Löschkonzepte
Datenverarbeitung in der Cloud
Anforderungen Arbeit im Home Office
Technische Gestaltung von Websites, Umgang mit Cookies
Verarbeitungsverzeichnisse erstellen, und auf Auftragsverarbeitung
Auskunftsfplichten nachkommen
Umgang mit Daten der Mitarbeiter*innen
Compliance-Vorschriften beachten und Umgang mit Regelverstößen
Strafrechtliche Risiken für Admins

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