Название: Security and Privacy in Federated Learning
Автор: Shui Yu, Lei Cui
Издательство: Springer
Год: 2023
Страниц: 142
Язык: английский
Формат: pdf (true), epub
Размер: 16.2 MB

In this book, the authors highlight the latest research findings on the security and privacy of Federated Learning systems. The main attacks and counterattacks in this booming field are presented to readers in connection with inference, poisoning, generative adversarial networks, differential privacy, secure multi-party computation, homomorphic encryption, and shuffle, respectively. In general, Federated Learning (FL) is a branch of Deep Learning, which is a powerful tool to address various complex problems in the past decades. Google proposed Federated Learning as a variation of Deep Learning in order to address the privacy concern from data owners. Federated Learning (FL) is a big step for privacy protection in Machine Learning; however, it is not perfect. The Federated Learning framework allows learning participants to keep their data locally and download the training model from a central server or servers to execute a local training. The updates will be uploaded to the server(s) for a further aggregation for the next round of training until an acceptable global model is reached. Despite the advancement of its computing model, Federated Learning still faces many security and privacy challenges, which have attracted a lot of attention from academia and industry.

Название: Introduction to Machine Learning with Python
Автор: Deepti Chopra, Roopal Khurana
Издательство: Bentham Books
Год: 2023
Страниц: 139
Язык: английский
Формат: pdf (true), epub
Размер: 27.3 MB

Machine Learning is a subfield of Artificial Intelligence (AI), broadly defined as a machine's capability to imitate intelligent human behavior. Like humans, machines become capable of making intelligent decisions by learning from their past experiences. Machine Learning is being employed in many applications, including fraud detection and prevention, self-driving cars, recommendation systems, facial recognition technology, and intelligent computing. This book helps beginners learn the art and science of Machine Learning. It presens real-world examples that leverage the popular Python Machine Learning ecosystem. The topics covered in this book include Machine Learning basics: supervised and unsupervised learning, linear regression and logistic regression, Support Vector Machines (SVMs). It also delves into special topics such as neural networks, theory of generalisation, and bias and fairness in Machine Learning. After reading this book, Computer Science and engineering students - at college and university levels - will receive a complete understanding.

Название: Applied Numerical Methods Using MATLAB
Автор: R.V. Dukkipati, PhD
Издательство: Mercury Learning and Information
Год: 2023
Страниц: 1225
Язык: английский
Формат: pdf (true)
Размер: 14.5 MB

The book is designed to cover all major aspects of applied numerical methods, including numerical computations, solution of algebraic and transcendental equations, finite differences and interpolation, curve fitting, correlation and regression, numerical differentiation and integration, matrices and linear system of equations, numerical solution of ordinary differential equations, and numerical solution of partial differential equations. MATLAB is incorporated throughout the text and most of the problems are executed in MATLAB code. It uses a numerical problem-solving orientation with numerous examples, figures, and end of chapter exercises. Presentations are limited to very basic topics to serve as an introduction to more advanced topics.

Название: Cloud Observability in Action (MEAP v7)
Автор: Michael Hausenblas
Издательство: Manning Publications
Год: 2023
Страниц: 179
Язык: английский
Формат: pdf (true)
Размер: 48.2 MB

Generate actionable insights about your cloud native systems. This book teaches you how to set up an observability system that learns from a cloud application’s signals, logging, and monitoring using free and open source tools. Cloud native, serverless, and containerized applications are made up of hundreds of moving parts. When something goes wrong, it’s not enough to just know there is a problem—you need to know where it is, what it is, and even how to fix it. Cloud Observability in Action shows you how to go beyond the traditional monitoring and build observability systems that turn application telemetry into actionable insight. Throughout the book, I’m using open source tooling including but not limited to OpenTelemetry (collector), Prometheus, Loki, Jaeger, and Grafana to demonstrate the different concepts and enable you to experiment with them, without any costs, other than your time.

Название: Kubernetes for Developers (MEAP v13)
Автор: William Denniss
Издательство: Manning Publications
Год: 2023
Страниц: 286
Язык: английский
Формат: pdf (true)
Размер: 39.7 MB

Kubernetes for Developers is a hands-on guide to taking your first steps into Kubernetes using the powerful Google Kubernetes Engine service. Kubernetes for Developers is a clear and practical beginner’s guide that shows you just how easy, flexible, and cost-effective it can be to make the switch to Kubernetes deployment even for small to medium-sized applications. Kubernetes for Developers is a hands-on guide to taking your first steps into Kubernetes using the powerful Google Kubernetes Engine service. It lays out a map for taking an application, containerizing it, and then deploying it onto Kubernetes. You’ll learn best practice techniques for a stable and long-term Kubernetes deployment, including scaling and capacity planning, saving money by optimizing resource consumption, and tricks to make your day-to-day monitoring easier such as debugging code in the cloud.

Название: Creating Software with Modern Diagramming Techniques: Build Better Software with Mermaid
Автор: Ashley Peacock
Издательство: Pragmatic Bookshelf
Год: February 2023 (Version: P1.0)
Страниц: 249
Язык: английский
Формат: pdf, epub
Размер: 10.2 MB

Diagrams communicate relationships more directly and clearly than words ever can. Using only text-based markup, create meaningful and attractive diagrams to document your domain, visualize user flows, reveal system architecture at any desired level, or refactor your code. With the tools and techniques this book will give you, you'll create a wide variety of diagrams in minutes, share them with others, and revise and update them immediately on the basis of feedback. Adding diagrams to your professional vocabulary will enable you to work through your ideas quickly when working on your own code or discussing a proposal with colleagues. We’ll start out by introducing most of the key concepts used throughout the book: Mermaid and UML. We’ll cover a brief history of UML, get you set up with Mermaid, and even produce your first diagram! Why Mermaid over other tools, such as PlantUML? Some of this will become apparent in later chapters, particularly the final one, but in the past PlantUML was a hard sell to engineers as there weren’t any major adoptions for it. Mermaid, however, in constrast is making waves, with GitHub and GitLab both having native support for rendering Mermaid diagrams without any additional tooling. Using tools like Mermaid, we can quickly and easily create an array of diagrams using syntax similar to Markdown.

Название: Alteryx Designer: The Definitive Guide (Ninth Early Release)
Автор: Joshua Burkhow
Издательство: O’Reilly Media, Inc.
Год: 2023-03-15
Страниц: 458
Язык: английский
Формат: epub (true), mobi
Размер: 33.4 MB

Analytics projects are frequently long-drawn-out affairs, requiring multiple teams and skills to clean, join, and eventually turn data into analysis for timely decision-making. Alteryx Designer changes all of that. With this low-code, self-service, drag-and-drop workflow platform, new and experienced data and business analysts can deliver results in hours instead of weeks. This practical book shows you how to master all areas of Alteryx Designer quickly. Author and Alteryx ACE Joshua Burkhow starts with the basics of building a workflow, then introduces more than 200 tools for working with intermediate and advanced analytics functionality. With Alteryx Designer's all-in-one toolkit, you'll migrate from legacy analytics software or Excel with ease.

Название: A Critical Understanding of Artificial Intelligence: A Phenomenological Foundation
Автор: Algis Mickunas, Joseph Pilotta
Издательство: Bentham Books
Год: 2023
Страниц: 264
Язык: английский
Формат: pdf (true), epub
Размер: 10.2 MB

Artificial Intelligence (AI) is viewed as one of the technological advances that will reshape modern societies and their relations. While the design and deployment of systems that continually adapt hold the promise of far-reaching, positive change, they simultaneously pose significant risks, especially to already vulnerable people. This work explores the meaning of AI, and the important role of critical understanding and its phenomenological foundation in shaping its ongoing advances. The values, power, and magic of reason are central to this discussion. Critical theory has used historical hindsight to explain the patterns of power that shape our intellectual, political, economic, and social worlds, and the discourse on AI that surrounds these worlds. The authors also delve into niche topics in philosophy such as transcendental self-awareness, post-humanism, and concepts of space-time and computer logic.

Название: Mobile Computing Solutions for Healthcare Systems
Автор: Sivakumar R., Dimiter Velev, Basim Alhadidi, S. Vidhya
Издательство: Bentham Books
Год: 2023
Страниц: 247
Язык: английский
Формат: pdf (true)
Размер: 41.4 MB

Mobile Health (M-Health) integrates the Internet of Things, mobile computing, medical image processing, medical sensor, and communications technology for mobile healthcare applications. Wireless Body Area Networks (WBANs) of intelligent sensors represent an emerging technology for system integration with great potential for unobtrusive ambulatory health monitoring during extended periods. However, system designers will have to resolve several issues, such as severe limitations of sensor weight and size necessary to improve user compliance, sensor resource constraints, intermittent availability of uplink connectivity, and reliability of transmission, security, and interoperability of different platforms. In addition, there are many challenges like Frequency Band Selection, Antenna Design, Channel Modelling, Energy-efficient hardware, Real-time connectivity over heterogeneous networks Security and Privacy, and others. With the WBAN placed on the patient body in rural areas and the mobile computing devices having the intelligence to acquire and process the data immediately, some of the issues like security and privacy are overcome. More intelligent processing is made available in handheld devices by building more facilities in the device software. This book focuses on recent developments in integrating AI, machine learning methods, medical image processing, advanced network security, and advanced antenna design techniques to bring M-Healthcare systems, leading to a new, promising, and secure M-Healthcare system.

Название: Machine Learning Algorithms in Depth (MEAP v7)
Автор: Vadim Smolyakov
Издательство: Manning Publications
Год: 2023
Страниц: 267
Язык: английский
Формат: pdf (true)
Размер: 46.1 MB

Develop a mathematical intuition for how Machine Learning (ML) algorithms work so you can improve model performance and effectively troubleshoot complex ML problems. Machine Learning Algorithms in Depth dives into the design and underlying principles of some of the most exciting Machine Learning (ML) algorithms in the world today. With a particular emphasis on probability-based algorithms, you’ll learn the fundamentals of Bayesian inference and Deep Learning. You’ll also explore the core data structures and algorithmic paradigms for Machine Learning. Each algorithm is fully explored with both math and practical implementations so you can see how they work and how they’re put into action. For each category of algorithm, you’ll go from math-first principles to a hands-on implementation in Python, exploring dozens of examples from across all the fields of machine learning. Each example is accompanied by worked-out derivations and details, as well as insightful code samples and graphics.