Informatyka
Network Scanning Cookbook. Practical network security using Nmap and Nessus 7
Sairam Jetty
Network scanning is a discipline of network security that identifies active hosts on networks and determining whether there are any vulnerabilities that could be exploited. Nessus and Nmap are among the top tools that enable you to scan your network for vulnerabilities and open ports, which can be used as back doors into a network.Network Scanning Cookbook contains recipes for configuring these tools in your infrastructure that get you started with scanning ports, services, and devices in your network. As you progress through the chapters, you will learn how to carry out various key scanning tasks, such as firewall detection, OS detection, and access management, and will look at problems related to vulnerability scanning and exploitation in the network. The book also contains recipes for assessing remote services and the security risks that they bring to a network infrastructure.By the end of the book, you will be familiar with industry-grade tools for network scanning, and techniques for vulnerability scanning and network protection.
David Knickerbocker
Network analysis is often taught with tiny or toy data sets, leaving you with a limited scope of learning and practical usage. Network Science with Python helps you extract relevant data, draw conclusions and build networks using industry-standard – practical data sets. You’ll begin by learning the basics of natural language processing, network science, and social network analysis, then move on to programmatically building and analyzing networks. You’ll get a hands-on understanding of the data source, data extraction, interaction with it, and drawing insights from it. This is a hands-on book with theory grounding, specific technical, and mathematical details for future reference. As you progress, you’ll learn to construct and clean networks, conduct network analysis, egocentric network analysis, community detection, and use network data with machine learning. You’ll also explore network analysis concepts, from basics to an advanced level. By the end of the book, you’ll be able to identify network data and use it to extract unconventional insights to comprehend the complex world around you.
Network Security with pfSense. Architect, deploy, and operate enterprise-grade firewalls
Manuj Aggarwal
While connected to the internet, you’re a potential target for an array of cyber threats, such as hackers, keyloggers, and Trojans that attack through unpatched security holes. A firewall works as a barrier (or ‘shield’) between your computer and cyberspace. pfSense is highly versatile firewall software. With thousands of enterprises using pfSense, it is fast becoming the world's most trusted open source network security solution.Network Security with pfSense begins with an introduction to pfSense, where you will gain an understanding of what pfSense is, its key features, and advantages. Next, you will learn how to configure pfSense as a firewall and create and manage firewall rules. As you make your way through the chapters, you will test pfSense for failover and load balancing across multiple wide area network (WAN) connections. You will then configure pfSense with OpenVPN for secure remote connectivity and implement IPsec VPN tunnels with pfSense. In the concluding chapters, you’ll understand how to configure and integrate pfSense as a Squid proxy server.By the end of this book, you will be able to leverage the power of pfSense to build a secure network.
Network Security with pfSense. Architect, deploy, and operate enterprise-grade firewalls
Manuj Aggarwal
While connected to the internet, you’re a potential target for an array of cyber threats, such as hackers, keyloggers, and Trojans that attack through unpatched security holes. A firewall works as a barrier (or ‘shield’) between your computer and cyberspace. pfSense is highly versatile firewall software. With thousands of enterprises using pfSense, it is fast becoming the world's most trusted open source network security solution.Network Security with pfSense begins with an introduction to pfSense, where you will gain an understanding of what pfSense is, its key features, and advantages. Next, you will learn how to configure pfSense as a firewall and create and manage firewall rules. As you make your way through the chapters, you will test pfSense for failover and load balancing across multiple wide area network (WAN) connections. You will then configure pfSense with OpenVPN for secure remote connectivity and implement IPsec VPN tunnels with pfSense. In the concluding chapters, you’ll understand how to configure and integrate pfSense as a Squid proxy server.By the end of this book, you will be able to leverage the power of pfSense to build a secure network.
Network Vulnerability Assessment. Identify security loopholes in your network's infrastructure
Sagar Rahalkar
The tech world has been taken over by digitization to a very large extent, and so it’s become extremely important for an organization to actively design security mechanisms for their network infrastructures. Analyzing vulnerabilities can be one of the best ways to secure your network infrastructure.Network Vulnerability Assessment starts with network security assessment concepts, workflows, and architectures. Then, you will use open source tools to perform both active and passive network scanning. As you make your way through the chapters, you will use these scanning results to analyze and design a threat model for network security. In the concluding chapters, you will dig deeper into concepts such as IP network analysis, Microsoft Services, and mail services. You will also get to grips with various security best practices, which will help you build your network security mechanism.By the end of this book, you will be in a position to build a security framework fit for an organization.
Gordon Davies
A network is a collection of computers, servers, mobile devices, or other computing devices connected for sharing data. This book will help you become well versed in basic networking concepts and prepare to pass Microsoft's MTA Networking Fundamentals Exam 98-366.Following Microsoft's official syllabus, the book starts by covering network infrastructures to help you differentiate intranets, internets, and extranets, and learn about network topologies. You’ll then get up to date with common network hardware devices such as routers and switches and the media types used to connect them together. As you advance, the book will take you through different protocols and services and the requirements to follow a standardized approach to networking. You’ll get to grips with the OSI and TCP/IP models as well as IPv4 and IPv6. The book also shows you how to recall IP addresses through name resolution. Finally, you’ll be able to practice everything you’ve learned and take the exam confidently with the help of mock tests. By the end of this networking book, you’ll have developed a strong foundation in the essential networking concepts needed to pass Exam 98-366.
Manpreet Singh Ghotra, Rajdeep Dua
If you're aware of the buzz surrounding the terms such as machine learning, artificial intelligence, or deep learning, you might know what neural networks are. Ever wondered how they help in solving complex computational problem efficiently, or how to train efficient neural networks? This book will teach you just that.You will start by getting a quick overview of the popular TensorFlow library and how it is used to train different neural networks. You will get a thorough understanding of the fundamentals and basic math for neural networks and why TensorFlow is a popular choice Then, you will proceed to implement a simple feed forward neural network. Next you will master optimization techniques and algorithms for neural networks using TensorFlow. Further, you will learn to implement some more complex types of neural networks such as convolutional neural networks, recurrent neural networks, and Deep Belief Networks. In the course of the book, you will be working on real-world datasets to get a hands-on understanding of neural network programming. You will also get to train generative models and will learn the applications of autoencoders.By the end of this book, you will have a fair understanding of how you can leverage the power of TensorFlow to train neural networks of varying complexities, without any hassle. While you are learning about various neural network implementations you will learn the underlying mathematics and linear algebra and how they map to the appropriate TensorFlow constructs.
James Loy
Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them.It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch.By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio.
V Kishore Ayyadevara
This book will take you from the basics of neural networks to advanced implementations of architectures using a recipe-based approach.We will learn about how neural networks work and the impact of various hyper parameters on a network's accuracy along with leveraging neural networks for structured and unstructured data.Later, we will learn how to classify and detect objects in images. We will also learn to use transfer learning for multiple applications, including a self-driving car using Convolutional Neural Networks.We will generate images while leveraging GANs and also by performing image encoding. Additionally, we will perform text analysis using word vector based techniques. Later, we will use Recurrent Neural Networks and LSTM to implement chatbot and Machine Translation systems.Finally, you will learn about transcribing images, audio, and generating captions and also use Deep Q-learning to build an agent that plays Space Invaders game.By the end of this book, you will have developed the skills to choose and customize multiple neural network architectures for various deep learning problems you might encounter.
Neural Networks with R. Build smart systems by implementing popular deep learning models in R
Balaji Venkateswaran, Giuseppe Ciaburro
Neural networks are one of the most fascinating machine learning models for solving complex computational problems efficiently. Neural networks are used to solve wide range of problems in different areas of AI and machine learning.This book explains the niche aspects of neural networking and provides you with foundation to get started with advanced topics. The book begins with neural network design using the neural net package, then you’ll build a solid foundation knowledge of how a neural network learns from data, and the principles behind it. This book covers various types of neural network including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks, but will also explore generalization of these networks. Later we will delve into combining different neural network models and work with the real-world use cases.By the end of this book, you will learn to implement neural network models in your applications with the help of practical examples in the book.
Neuro-Symbolic AI. Design transparent and trustworthy systems that understand the world as you do
Alexiei Dingli, David Farrugia
Neuro-symbolic AI offers the potential to create intelligent systems that possess both the reasoning capabilities of symbolic AI along with the learning capabilities of neural networks. This book provides an overview of AI and its inner mechanics, covering both symbolic and neural network approaches.You’ll begin by exploring the decline of symbolic AI and the recent neural network revolution, as well as their limitations. The book then delves into the importance of building trustworthy and transparent AI solutions using explainable AI techniques. As you advance, you’ll explore the emerging field of neuro-symbolic AI, which combines symbolic AI and modern neural networks to improve performance and transparency. You’ll also learn how to get started with neuro-symbolic AI using Python with the help of practical examples. In addition, the book covers the most promising technologies in the field, providing insights into the future of AI.Upon completing this book, you will acquire a profound comprehension of neuro-symbolic AI and its practical implications. Additionally, you will cultivate the essential abilities to conceptualize, design, and execute neuro-symbolic AI solutions.
Tomasz Rymarczyk Krzysztof Król
This publication was prepared as a permanent record of research findings presented by doctoral students and academics representing diverse research backgrounds and schools. The focus is on interdisciplinary solutions, combining engineering, computer science, and mathematical methods with approaches relevant to management science and socio-economic applications. The International Interdisciplinary PhD Workshop (IIPhDW) is a cyclical and international conference, and its primary function is to provide a platform for research presentations, knowledge exchange, and collaboration between young scientists from various disciplines. The 2025 edition featured a particularly strong technical component, encompassing artificial intelligence, computer science, automation and control, robotics and mechatronics, telecommunications, signal processing, as well as mechanical and production engineering. At the same time, the inclusion of topics in economics and management confirmed the workshop's broad scope and its ability to integrate research perspectives relevant to contemporary technological and organizational challenges. A significant group of publications includes works on process and biomedical tomography, as well as image reconstruction methods using machine learning and deep learning, including approaches combining physical models with neural network architectures. Examples include research on image reconstruction in electrical impedance tomography, the integration of tomography with neural networks for industrial process monitoring, and the use of ultrasound tomography in measurement and reconstruction analysis. This theme is further reinforced by works on hybrid tomography systems, process monitoring using mixed reality technology, and applications in the areas of physiological parameter monitoring and non-invasive diagnostics. The second recognizable axis is artificial intelligence in IT and cyberphysical systems, encompassing both the construction of predictive and classification models and their implementation in industrial, medical, and service environments. This trend includes work related to the application of machine learning methods in system and network security, solutions based on LLM agents in project team workflows, processing unstructured data using OCR and language models, and multimodal analysis in intelligent customer service systems. This perspective highlights the contemporary trend of convergence of AI techniques with data engineering, software engineering, and systems integration, which has direct implications for the design of scalable implementation solutions. The third thematic area covers embedded systems, communication, and signal processing, along with elements of computational resource optimization. The monograph includes papers on, among other things, phase shift estimation in noisy environments, pseudorandom sequence generation, acoustic feature detection, and the efficiency of machine learning applications at the network edge in the context of Kubernetes scheduling heuristics. In the monograph, this strand serves a methodological purpose, providing signal analysis tools and computational mechanisms that form the foundation for many AI and measurement system applications. A significant complement to the technical perspective are works in the areas of management and organizational and economic analysis, which address the need to understand the determinants of technology implementation and the conduct of innovative projects. The publications address, among other things, the predictors of success in startup management and the analysis of organizational improvements in public institutions. Their presence strengthens the interdisciplinary nature of the monograph by demonstrating that the effectiveness of engineering solutions depends not only on the quality of algorithms and devices, but also on the organizational, process, and decision-making context. The monograph is intended as a reference for academics and doctoral students, particularly those seeking examples of research that combines theory with application. The collected papers offer a comprehensive overview of research activities typical of early careers in science, from conceptual studies and method analysis, through device and software architecture prototyping, to experiments and evaluation of the effectiveness of proposed solutions. At the same time, the publication allows for the identification of common methodological denominators, such as the growing importance of measurement data, simulation, deep learning, systems integration, and the pursuit of real-time operation in industrial and biomedical environments. The introduction, on the one hand, contextualizes the monograph within the mission of IIPhDW as a workshop supporting researcher development and the internationalization of research. On the other hand, it organizes the chapter topics in the perspective of dominant technological trends and application needs that permeate various fields. Consequently, the monograph can be viewed as a synthetic overview of current research directions for doctoral students and young academics, as well as an inspiration for undertaking work combining artificial intelligence methods, measurement systems, software engineering, and management analyses within modern interdisciplinary projects.
Susan Nelson Spencer
The field of instructional design offers a rapidly growing, flexible, and rewarding career path. Chances are that if you’re a teacher creating training material, college professor designing educational courses, human resources professional creating learning content, or even a graphic designer curating content, you may already be engaging in instructional designing without even realizing it!This book teaches you all about the four capabilities that are most important to exceling as an instructional designer—teaching, writing, creating, and analyzing. The chapters are designed in a way that provides you with practical tips for day-to-day learning projects through true ID stories. You’ll get familiar with common misconceptions surrounding the field, along with how to overcome your shortcomings. With the help of easy-to-understand real-world case studies and practical tips, each chapter focuses on developing one particular competency to help you grasp the concepts with ease.By the end of this book, you’ll have gained a comprehensive understanding of the key competencies needed to succeed in this field and their importance, and learned how to develop them effectively.
Dale Nguyen
Elevate your UI development skills with Next-Level UI Development with PrimeNG. In a digital landscape where the user interface plays a pivotal role, PrimeNG expertise is essential for Angular developers. This all-encompassing book shows you how to unleash this powerful UI component library in your Angular projects.From the initial setup to integration, you'll explore the synergy between Angular and PrimeNG and how it can help you enhance your projects. You’ll work with a wide range of UI components and features, such as input controls, data display, manipulation, and navigation, which allow you to build intuitive and dynamic user interfaces. You'll also discover advanced techniques and best practices for theming, performance optimization, creating reusable components, and handling internationalization and localization. With insights into testing and debugging PrimeNG components, this book ensures the development of robust and error-free applications, and finally guides you toward putting your knowledge into practice by building a real-world responsive web application.By the end of this book, you will be able to harness the full potential of PrimeNG, enabling you to create extraordinary web experiences that stand out from the rest.
Dave West, Kurt Bittner, Patricia Kong
Popraw i przyspiesz dostarczanie oprogramowania w dużych, rozproszonych i złożonych projektach Nexus to najprostsze i najskuteczniejsze podejście do stosowania Scruma w skali obejmującej wiele zespołów, lokalizacji i stref czasowych. Został utworzony przez Scrum.org pionierską organizację prowadzącą szkolenia i przyznającą certyfikaty dotyczące Scruma. Organizację tę założył Ken Schwaber, współtwórca Scrum. Podczas tworzenia Nexusa wykorzystano dekady doświadczenia, stawiając czoła wyjątkowym wyzwaniom, z którymi mierzą się zespoły, łącząc się, współdzieląc pracę, zarządzając i minimalizując zależności. Nexus, czyli skalowalny Scrum to zwięzła książka, która pokazuje, jak Nexus pomaga zespołom dostarczać złożone, wieloplatformowe, programistyczne produkty w krótkich, częstych cyklach, nie poświęcając spójności ani jakości, nie dodając niepotrzebnej złożoności i nie odchodząc od zasadniczych założeń Scrum. W rozbudowanym studium przypadku autorzy zilustrowali, jak Nexus pomaga rozwiązać typowe wyzwania związane ze skalowaniem, w tym redukcję zależności między zespołami, zachowanie samoorganizacji zespołów i utrzymanie przejrzystości, ta także sprawozdawczość. Zrozum wyzwania dotyczące dostarczania pracy, zintegrowanych przyrostów produktu pochodzących od wielu zespołów oraz dowiedz się, jak odnosi się do nich Nexus. Utwórz Nexus wokół nowego lub istniejącego produktu i naucz się definiować cele i planować pracę zgodnie z Nexusem. Uruchom sprinty w Nexusie, zapewniając przejrzystość postępu, prowadząc skuteczne przeglądy sprintów Nexusa i używając retrospektyw sprintów Nexusa w celu ciągłego udoskonalania. Pokonaj wyzwania związane ze współpracą rozproszonych zespołów.
NGINX Cookbook. Over 70 recipes for real-world configuration, deployment, and performance
Tim Butler
NGINX Cookbook covers the basics of configuring NGINX as a web server for use with common web frameworks such as WordPress and Ruby on Rails, through to utilization as a reverse proxy. Designed as a go-to reference guide, this book will give you practical answers based on real-world deployments to get you up and running quickly. Recipes have also been provided for multiple SSL configurations, different logging scenarios, practical rewrites, and multiple load balancing scenarios. Advanced topics include covering bandwidth management, Docker container usage, performance tuning, OpenResty, and the NGINX Plus commercial features.By the time you've read this book, you will be able to adapt and use a wide variety of NGINX implementations to solve any problems you have.
Valery Kholodkov, Valery I Kholodkov
This book is ideal for skilled web masters and site reliability engineers who want to switch to Nginx or solidify their knowledge of Nginx. Knowledge of Unix and webmaster skills are required.