Verleger: K-i-s-publishing
The Universal Service Desk (USD). Implementing, controlling, and improving service delivery
IT Governance Publishing, Brian Johnson, Léon-Paul de...
This book is your go-to guide to mastering the Universal Service Desk (USD) for improving service management. The reader will understand USD's role in enterprises, delve into its design process, and learn how to use it for effective customer service and business operations. With practical examples and industry case studies, this book offers deep insights into the application of the USD for organizational success.The book begins by introducing the USD concept, highlighting its importance in streamlining service delivery and enhancing customer satisfaction. It outlines how a demand-oriented approach can be implemented across various business environments, optimizing workflows from front-office interactions to back-office coordination. Through the chapters, readers will learn to adapt USD to meet the evolving needs of enterprises.The final chapters focus on advanced practices such as improving service quality, managing virtual USD platforms, and aligning service desk operations with business goals. By following the structured approach outlined, you’ll gain the tools to create a USD that delivers measurable value, fosters seamless communication, and aligns with organizational priorities.
Aaron Jones, Christopher Kruger, Benjamin Johnston
Do you find it difficult to understand how popular companies like WhatsApp and Amazon find valuable insights from large amounts of unorganized data? The Unsupervised Learning Workshop will give you the confidence to deal with cluttered and unlabeled datasets, using unsupervised algorithms in an easy and interactive manner.The book starts by introducing the most popular clustering algorithms of unsupervised learning. You'll find out how hierarchical clustering differs from k-means, along with understanding how to apply DBSCAN to highly complex and noisy data. Moving ahead, you'll use autoencoders for efficient data encoding.As you progress, you’ll use t-SNE models to extract high-dimensional information into a lower dimension for better visualization, in addition to working with topic modeling for implementing natural language processing (NLP). In later chapters, you’ll find key relationships between customers and businesses using Market Basket Analysis, before going on to use Hotspot Analysis for estimating the population density of an area.By the end of this book, you’ll be equipped with the skills you need to apply unsupervised algorithms on cluttered datasets to find useful patterns and insights.
Benjamin Strout
Vulnerability researchers are in increasingly high demand as the number of security incidents related to crime continues to rise with the adoption and use of technology. To begin your journey of becoming a security researcher, you need more than just the technical skills to find vulnerabilities; you’ll need to learn how to adopt research strategies and navigate the complex and frustrating process of sharing your findings. This book provides an easy-to-follow approach that will help you understand the process of discovering, disclosing, and publishing your first zero-day vulnerability through a collection of examples and an in-depth review of the process.You’ll begin by learning the fundamentals of vulnerabilities, exploits, and what makes something a zero-day vulnerability. Then, you'll take a deep dive into the details of planning winning research strategies, navigating the complexities of vulnerability disclosure, and publishing your research with sometimes-less-than-receptive vendors.By the end of the book, you'll be well versed in how researchers discover, disclose, and publish vulnerabilities, navigate complex vendor relationships, receive credit for their work, and ultimately protect users from exploitation. With this knowledge, you’ll be prepared to conduct your own research and publish vulnerabilities.
Andrew Pease
Threat Hunting with Elastic Stack will show you how to make the best use of Elastic Security to provide optimal protection against cyber threats. With this book, security practitioners working with Kibana will be able to put their knowledge to work and detect malicious adversary activity within their contested network.You'll take a hands-on approach to learning the implementation and methodologies that will have you up and running in no time. Starting with the foundational parts of the Elastic Stack, you'll explore analytical models and how they support security response and finally leverage Elastic technology to perform defensive cyber operations.You’ll then cover threat intelligence analytical models, threat hunting concepts and methodologies, and how to leverage them in cyber operations. After you’ve mastered the basics, you’ll apply the knowledge you've gained to build and configure your own Elastic Stack, upload data, and explore that data directly as well as by using the built-in tools in the Kibana app to hunt for nefarious activities.By the end of this book, you'll be able to build an Elastic Stack for self-training or to monitor your own network and/or assets and use Kibana to monitor and hunt for adversaries within your network.
Threat Modeling Best Practices. Proven frameworks and practical techniques to secure modern systems
Derek Fisher
Threat modeling has become a cornerstone of modern cybersecurity, yet it is often overlooked, leaving security gaps that attackers can exploit. With the rise in system complexity, cloud adoption, AI-driven threats, and stricter compliance requirements, security teams need a structured approach to proactively spot and stop risks before attackers do. This book delivers exactly that, offering actionable insights for applying industry best practices and emerging technologies to secure systems. It breaks down the fundamentals of threat modeling and walks you through key frameworks and tools such as STRIDE, MITRE ATT&CK, PyTM, and Attack Paths, helping you choose the right model and create a roadmap tailored to your business. You'll learn how to use leading threat modeling tools, identify and prioritize potential threats, and integrate these practices into the software development life cycle to detect risks early. The book also examines how AI can enhance analysis and streamline security decision-making for faster, stronger defenses.By the end, you'll have everything you need to build systems that anticipate and withstand evolving threats, keeping your organization secure in an ever-changing digital landscape.*Email sign-up and proof of purchase required
Threat Modeling Gameplay with EoP. A reference manual for spotting threats in software architecture
Brett Crawley, Adam Shostack
Are you looking to navigate security risks, but want to make your learning experience fun? Here's a comprehensive guide that introduces the concept of play to protect, helping you discover the threats that could affect your software design via gameplay.Each chapter in this book covers a suit in the Elevation of Privilege (EoP) card deck (a threat category), providing example threats, references, and suggested mitigations for each card. You’ll explore the methodology for threat modeling—Spoofing, Tampering, Repudiation, Information Disclosure, and Elevation of Privilege (S.T.R.I.D.E.) with Privacy deck and the T.R.I.M. extension pack. T.R.I.M. is a framework for privacy that stands for Transfer, Retention/Removal, Inference, and Minimization. Throughout the book, you’ll learn the meanings of these terms and how they should be applied. From spotting vulnerabilities to implementing practical solutions, the chapters provide actionable strategies for fortifying the security of software systems.By the end of this book, you will be able to recognize threats, understand privacy regulations, access references for further exploration, and get familiarized with techniques to protect against these threats and minimize risks.
Gema Socorro Rodríguez
With resources on Android and Kotlin abound, it’s difficult to find content that focuses on resolving common challenges faced by app developers. This book by Gema Socorro Rodríguez – a Google Developer Expert for Android with over 15 years of experience and a proven track record as an effective instructor – is designed to bridge the gap between theory and real-world application. It equips you with the skills to tackle everyday problems in Android development through hands-on projects.Under Gema's expert guidance, you’ll build three sophisticated Android projects. You'll start your development journey by building a WhatsApp-like application, learning how to process asynchronous messages reactively, render them using Jetpack Compose, and advance to creating and uploading a backup of these messages. Next, you’ll channel your creativity into Packtagram, an Instagram-inspired app that offers advanced photo-editing capabilities using the latest CameraX libraries. Your final project will be a Netflix-style app, integrating video playback functionality with ExoPlayer for both foreground and background operations, and implementing device casting features.By the end of this book, you'll have crafted three fully functional, multi-platform projects and gained the confidence to solve the most common challenges in Android development.
Andrew Berridge, Michael Phillips
The need for agile business intelligence (BI) is growing daily, and TIBCO Spotfire® combines self-service features with essential enterprise governance and scaling capabilities to provide best-practice analytics solutions. Spotfire is easy and intuitive to use and is a rewarding environment for all BI users and analytics developers.Starting with data and visualization concepts, this book takes you on a journey through increasingly advanced topics to help you work toward becoming a professional analytics solution provider. Examples of analyzing real-world data are used to illustrate how to work with Spotfire. Once you've covered the AI-driven recommendations engine, you'll move on to understanding Spotfire's rich suite of visualizations and when, why and how you should use each of them. In later chapters, you'll work with location analytics, advanced analytics using TIBCO Enterprise Runtime for R®, how to decide whether to use in-database or in-memory analytics, and how to work with streaming (live) data in Spotfire. You'll also explore key product integrations that significantly enhance Spotfire's capabilities.This book will enable you to exploit the advantages of the Spotfire serve topology and learn how to make practical use of scheduling and routing rules.By the end of this book, you will have learned how to build and use powerful analytics dashboards and applications, perform spatial analytics, and be able to administer your Spotfire environment efficiently
Michaël Hoarau
Being a business analyst and data scientist, you have to use many algorithms and approaches to prepare, process, and build ML-based applications by leveraging time series data, but you face common problems, such as not knowing which algorithm to choose or how to combine and interpret them. Amazon Web Services (AWS) provides numerous services to help you build applications fueled by artificial intelligence (AI) capabilities. This book helps you get to grips with three AWS AI/ML-managed services to enable you to deliver your desired business outcomes.The book begins with Amazon Forecast, where you’ll discover how to use time series forecasting, leveraging sophisticated statistical and machine learning algorithms to deliver business outcomes accurately. You’ll then learn to use Amazon Lookout for Equipment to build multivariate time series anomaly detection models geared toward industrial equipment and understand how it provides valuable insights to reinforce teams focused on predictive maintenance and predictive quality use cases. In the last chapters, you’ll explore Amazon Lookout for Metrics, and automatically detect and diagnose outliers in your business and operational data.By the end of this AWS book, you’ll have understood how to use the three AWS AI services effectively to perform time series analysis.
Tarek A. Atwan
Time series data is everywhere, available at a high frequency and volume. It is complex and can contain noise, irregularities, and multiple patterns, making it crucial to be well-versed with the techniques covered in this book for data preparation, analysis, and forecasting.This book covers practical techniques for working with time series data, starting with ingesting time series data from various sources and formats, whether in private cloud storage, relational databases, non-relational databases, or specialized time series databases such as InfluxDB. Next, you’ll learn strategies for handling missing data, dealing with time zones and custom business days, and detecting anomalies using intuitive statistical methods, followed by more advanced unsupervised ML models. The book will also explore forecasting using classical statistical models such as Holt-Winters, SARIMA, and VAR. The recipes will present practical techniques for handling non-stationary data, using power transforms, ACF and PACF plots, and decomposing time series data with multiple seasonal patterns. Later, you’ll work with ML and DL models using TensorFlow and PyTorch.Finally, you’ll learn how to evaluate, compare, optimize models, and more using the recipes covered in the book.
Tarek A. Atwan
To use time series data to your advantage, you need to master data preparation, analysis, and forecasting. This fully refreshed second edition helps you unlock insights from time series data with new chapters on probabilistic models, signal processing techniques, and new content on transformers. You’ll work with the latest releases of popular libraries like Pandas, Polars, Sktime, stats models, stats forecast, Darts, and Prophet through up-to-date examples.You'll hit the ground running by ingesting time series data from various sources and formats and learn strategies for handling missing data, dealing with time zones and custom business days, and detecting anomalies using intuitive statistical methods.Through detailed instructions, you'll explore forecasting using classical statistical models such as Holt-Winters, SARIMA, and VAR, and learn practical techniques for handling non-stationary data using power transforms, ACF and PACF plots, and decomposing time series data with seasonal patterns. The recipes then level up to cover more advanced topics such as building ML and DL models using TensorFlow and PyTorch and applying probabilistic modeling techniques. In this part, you’ll also be able to evaluate, compare, and optimize models, finishing with a strong command of wrangling data with Python.
Yoni Ramaswami, Dael Williamson, Jan Govaere
Written by Databricks Senior Solutions Architect Yoni Ramaswami, whose expertise in Data and AI has shaped innovative digital transformations across industries, this comprehensive guide bridges foundational concepts of time series analysis with the Spark framework and Databricks, preparing you to tackle real-world challenges with confidence.From preparing and processing large-scale time series datasets to building reliable models, this book offers practical techniques that scale effortlessly for big data environments. You’ll explore advanced topics such as scaling your analyses, deploying time series models into production, Generative AI, and leveraging Spark's latest features for cutting-edge applications across industries. Packed with hands-on examples and industry-relevant use cases, this guide is perfect for data engineers, ML engineers, data scientists, and analysts looking to enhance their expertise in handling large-scale time series data.By the end of this book, you’ll have mastered the skills to design and deploy robust, scalable time series models tailored to your unique project needs—qualifying you to excel in the rapidly evolving world of big data analytics.*Email sign-up and proof of purchase required
Time Series Indexing. Implement iSAX in Python to index time series with confidence
Mihalis Tsoukalos
Time series are everywhere, ranging from financial data and system metrics to weather stations and medical records. Being able to access, search, and compare time series data quickly is essential, and this comprehensive guide enables you to do just that by helping you explore SAX representation and the most effective time series index, iSAX.The book begins by teaching you about the implementation of SAX representation in Python as well as the iSAX index, along with the required theory sourced from academic research papers. The chapters are filled with figures and plots to help you follow the presented topics and understand key concepts easily. But what makes this book really great is that it contains the right amount of knowledge about time series indexing using the right amount of theory and practice so that you can work with time series and develop time series indexes successfully. Additionally, the presented code can be easily ported to any other modern programming language, such as Swift, Java, C, C++, Ruby, Kotlin, Go, Rust, and JavaScript.By the end of this book, you'll have learned how to harness the power of iSAX and SAX representation to efficiently index and analyze time series data and will be equipped to develop your own time series indexes and effectively work with time series data.
Gian Marco Iodice, Ronan Naughton
This book explores TinyML, a fast-growing field at the unique intersection of machine learning and embedded systems to make AI ubiquitous with extremely low-powered devices such as microcontrollers.The TinyML Cookbook starts with a practical introduction to this multidisciplinary field to get you up to speed with some of the fundamentals for deploying intelligent applications on Arduino Nano 33 BLE Sense and Raspberry Pi Pico. As you progress, you’ll tackle various problems that you may encounter while prototyping microcontrollers, such as controlling the LED state with GPIO and a push-button, supplying power to microcontrollers with batteries, and more. Next, you’ll cover recipes relating to temperature, humidity, and the three “V” sensors (Voice, Vision, and Vibration) to gain the necessary skills to implement end-to-end smart applications in different scenarios. Later, you’ll learn best practices for building tiny models for memory-constrained microcontrollers. Finally, you’ll explore two of the most recent technologies, microTVM and microNPU that will help you step up your TinyML game.By the end of this book, you’ll be well-versed with best practices and machine learning frameworks to develop ML apps easily on microcontrollers and have a clear understanding of the key aspects to consider during the development phase.