Informatyka
Aditya Bhattacharya
Explainable AI (XAI) is an emerging field that brings artificial intelligence (AI) closer to non-technical end users. XAI makes machine learning (ML) models transparent and trustworthy along with promoting AI adoption for industrial and research use cases.Applied Machine Learning Explainability Techniques comes with a unique blend of industrial and academic research perspectives to help you acquire practical XAI skills. You'll begin by gaining a conceptual understanding of XAI and why it's so important in AI. Next, you'll get the practical experience needed to utilize XAI in AI/ML problem-solving processes using state-of-the-art methods and frameworks. Finally, you'll get the essential guidelines needed to take your XAI journey to the next level and bridge the existing gaps between AI and end users.By the end of this ML book, you'll be equipped with best practices in the AI/ML life cycle and will be able to implement XAI methods and approaches using Python to solve industrial problems, successfully addressing key pain points encountered.
Ujjwal Ratan
While machine learning is not new, it's only now that we are beginning to uncover its true potential in the healthcare and life sciences industry. The availability of real-world datasets and access to better compute resources have helped researchers invent applications that utilize known AI techniques in every segment of this industry, such as providers, payers, drug discovery, and genomics.This book starts by summarizing the introductory concepts of machine learning and AWS machine learning services. You’ll then go through chapters dedicated to each segment of the healthcare and life sciences industry. Each of these chapters has three key purposes -- First, to introduce each segment of the industry, its challenges, and the applications of machine learning relevant to that segment. Second, to help you get to grips with the features of the services available in the AWS machine learning stack like Amazon SageMaker and Amazon Comprehend Medical. Third, to enable you to apply your new skills to create an ML-driven solution to solve problems particular to that segment. The concluding chapters outline future industry trends and applications.By the end of this book, you’ll be aware of key challenges faced in applying AI to healthcare and life sciences industry and learn how to address those challenges with confidence.
Applied Network Security. Proven tactics to detect and defend against all kinds of network attack
Warun Levesque, Arthur Salmon, Michael McLafferty
Computer networks are increasing at an exponential rate and the most challenging factor organisations are currently facing is network security. Breaching a network is not considered an ingenious effort anymore, so it is very important to gain expertise in securing your network.The book begins by showing you how to identify malicious network behaviour and improve your wireless security. We will teach you what network sniffing is, the various tools associated with it, and how to scan for vulnerable wireless networks. Then we’ll show you how attackers hide the payloads and bypass the victim’s antivirus. Furthermore, we’ll teach you how to spoof IP / MAC address and perform an SQL injection attack and prevent it on your website. We will create an evil twin and demonstrate how to intercept network traffic. Later, you will get familiar with Shodan and Intrusion Detection and will explore the features and tools associated with it. Toward the end, we cover tools such as Yardstick, Ubertooth, Wifi Pineapple, and Alfa used for wireless penetration testing and auditing. This book will show the tools and platform to ethically hack your own network whether it is for your business or for your personal home Wi-Fi.
Alok Malik, Bradford Tuckfield
Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and features of R that enable you to understand your data better and get answers to your most pressing business questions. This book begins with the most important and commonly used method for unsupervised learning - clustering - and explains the three main clustering algorithms - k-means, divisive, and agglomerative. Following this, you'll study market basket analysis, kernel density estimation, principal component analysis, and anomaly detection. You'll be introduced to these methods using code written in R, with further instructions on how to work with, edit, and improve R code. To help you gain a practical understanding, the book also features useful tips on applying these methods to real business problems, including market segmentation and fraud detection. By working through interesting activities, you'll explore data encoders and latent variable models. By the end of this book, you will have a better understanding of different anomaly detection methods, such as outlier detection, Mahalanobis distances, and contextual and collective anomaly detection.
Simon Greener, Siva Ravada
Spatial applications should be developed in the same way that users develop other database applications: by starting with an integrated data model in which the SDO_GEOMETRY objects are just another attribute describing entities and by using as many of the database features as possible for managing the data. If a task can be done using a database feature like replication, then it should be done using the standard replication technology instead of inventing a new procedure for replicating spatial data. Sometimes solving a business problem using a PL/SQL function can be more powerful, accessible, and easier to use than trying to use external software. Because Oracle Spatial's offerings are standards compliant, this book shows you how Oracle Spatial technology can be used to build cross-vendor database solutions. Applying and Extending Oracle Spatial shows you the clever things that can be done not just with Oracle Spatial on its own, but in combination with other database technologies. This is a great resource book that will convince you to purchase other Oracle technology books on non-spatial specialist technologies because you will finally see that spatial is not special: it is a small, fun, and clever part of a much larger whole.
Mercury Learning and Information, Paul Boudreau
Artificial intelligence is reshaping the way projects are managed, offering unprecedented opportunities to improve efficiency, accuracy, and outcomes. This course begins with an introduction to AI’s role in project management, exploring how machine learning, natural language processing, and predictive algorithms can transform traditional approaches. You’ll learn about the key components of AI-driven projects and how to develop a strong business case for adopting these innovations.As you progress, the course delves into practical applications of AI in automating project tasks, analyzing data, and predicting results. Participants will gain hands-on experience with tools that leverage machine learning to forecast project success, improve productivity, and resolve potential failures. Additionally, you’ll discover how generative AI and large language models can enhance communication, planning, and decision-making throughout the project lifecycle.Finally, the course examines the broader implications of integrating AI into project management. You’ll explore strategies for acquiring AI solutions, implementing them within teams, and navigating the ethical challenges they present. By the end of the course, participants will have a clear understanding of how to leverage AI to optimize projects and stay competitive in a rapidly evolving technological landscape.
Sam Morley
The updated edition of Applying Math with Python will help you solve complex problems in a wide variety of mathematical fields in simple and efficient ways. Old recipes have been revised for new libraries and several recipes have been added to demonstrate new tools such as JAX.You'll start by refreshing your knowledge of several core mathematical fields and learn about packages covered in Python's scientific stack, including NumPy, SciPy, and Matplotlib. As you progress, you'll gradually get to grips with more advanced topics of calculus, probability, and networks (graph theory). Once you’ve developed a solid base in these topics, you’ll have the confidence to set out on math adventures with Python as you explore Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code.By the end of this book, you'll have an arsenal of practical coding solutions that can be used and modified to solve a wide range of practical problems in computational mathematics and data science.
Mark J. Price
Elevate your practical C# and .NET skills to the next level with this new edition of Apps and Services with .NET 8.With chapters that put a variety of technologies into practice, including Web API, gRPC, GraphQL, and SignalR, this book will give you a broader scope of knowledge than other books that often focus on only a handful of .NET technologies. You’ll dive into the new unified model for Blazor Full Stack and leverage .NET MAUI to develop mobile and desktop apps.This new edition introduces the latest enhancements, including the seamless implementation of web services with ADO.NET SqlClient's native Ahead-of-Time (AOT) support. Popular library coverage now includes Humanizer and Noda Time. There’s also a brand-new chapter that delves into service architecture, caching, queuing, and robust background services.By the end of this book, you’ll have a wide range of best practices and deep insights under your belt to help you build rich apps and efficient services.*Email sign-up and proof of purchase required
Eric Pimpler
This book is an immersive guide to take your ArcGIS Desktop application development skills to the next levelIt starts off by providing detailed description and examples of how to create ArcGIS Desktop Python toolboxes that will serve as containers for many of the applications that you will build. We provide several practical projects that involve building a local area/community map and extracting wildfire data. You will then learn how to build tools that can access data from ArcGIS Server using the ArcGIS REST API. Furthermore, we deal with the integration of additional open source Python libraries into your applications, which will help you chart and graph advanced GUI development; read and write JSON, CSV, and XML format data sources; write outputs to Google Earth Pro, and more. Along the way, you will be introduced to advanced ArcPy Mapping and ArcPy Data Access module techniques and use data-driven Pages to automate the creation of map books.Finally, you will learn advanced techniques to work with video and social media feeds. By the end of the book, you will have your own desktop application without having spent too much time learning sophisticated theory.
Tripp Corbin, GISP
ArcGIS is Esri's catalog of GIS applications with powerful tools for visualizing, maintaining, and analyzing data. ArcGIS makes use of the modern ribbon interface and 64-bit processing to increase the speed and efficiency of using GIS. It allows users to create amazing maps in both 2D and 3D quickly and easily. If you want to gain a thorough understanding of the various data formats that can be used in ArcGIS Pro and shared via ArcGIS Online, then this book is for you. Beginning with a refresher on ArcGIS Pro and how to work with projects, this book will quickly take you through recipes about using various data formats supported by the tool. You will learn the limits of each format, such as Shapefiles, Geodatabase, and CAD files, and learn how to link tables from outside sources to existing GIS data to expand the amount of data that can be used in ArcGIS. You'll learn methods for editing 2D and 3D data using ArcGIS Pro and how topology can be used to ensure data integrity. Lastly the book will show you how data and maps can be shared via ArcGIS Online and used with web and mobile applications.
Tripp Corbin, GISP
ArcGIS is Esri's catalog of GIS applications with powerful tools for visualizing, maintaining, and analyzing data. ArcGIS makes use of the modern ribbon interface and 64-bit processing to increase the speed and efficiency of using GIS. It allows users to create amazing maps in both 2D and 3D quickly and easily. If you want to gain a thorough understanding of the various data formats that can be used in ArcGIS Pro and shared via ArcGIS Online, then this book is for you. Beginning with a refresher on ArcGIS Pro and how to work with projects, this book will quickly take you through recipes about using various data formats supported by the tool. You will learn the limits of each format, such as Shapefiles, Geodatabase, and CAD files, and learn how to link tables from outside sources to existing GIS data to expand the amount of data that can be used in ArcGIS. You'll learn methods for editing 2D and 3D data using ArcGIS Pro and how topology can be used to ensure data integrity. Lastly the book will show you how data and maps can be shared via ArcGIS Online and used with web and mobile applications.
ArchiCAD. Wprowadzenie do projektowania BIM
Rafał Ślęk
Architekci potrzebują właściwych narzędzi, a narzędzia — odpowiedniej dokumentacji. Oto ona! ArchiCAD to najczęściej wykorzystywane narzędzie wspomagające projektowanie architektoniczne. Uwielbiają je architekci i architekci krajobrazu oraz projektanci wnętrz. Łatwa i intuicyjna obsługa, duże możliwości, szeroki wybór specjalizowanych narzędzi do opracowywania dokumentacji 2D i 3D oraz funkcje umożliwiające tworzenie atrakcyjnych wizualizacji sprawiły, że środowisko to, rozwijane przez węgierską firmę Graphisoft, zagościło w biurach projektowych na całym świecie, a także zjednało sobie rzesze fanów wśród studentów kierunków architektonicznych, budowlanych i artystycznych. Korzystanie z ArchiCAD-a nie nastręcza wielkich trudności, ale - podobnie jak w przypadku każdego programu komputerowego - nauka może odbywać się czasochłonną metodą prób i błędów lub postępować znacznie szybciej, gdy dysponuje się odpowiednim źródłem wiedzy, takim jak książka „ArchiCAD. Wprowadzenie do projektowania BIM ”. Wprowadzi ona użytkownika w zagadnienia związane z projektowaniem architektonicznym, nauczy unikać częstych błędów i pozwoli nabrać doświadczenia umożliwiającego samodzielną pracę w programie. Publikacja stanowi doskonałe uzupełnienie systemu pomocy aplikacji, jak również praktyczny przewodnik po świecie nowoczesnej technologii modelowania informacji o budynku - BIM. Konfiguracja sprzętu i instalacja programu ArchiCAD Graficzny interfejs użytkownika aplikacji i jego składniki Organizacja pracy w środowisku ArchiCAD i zasady bezpieczeństwa Podstawowe możliwości tworzenia i edycji modelu Korzystanie z narzędzi do modelowania elementów budynku Tworzenie dokumentacji 2D na podstawie modelu Projektowanie architektoniczne jeszcze nigdy nie było tak proste!
Richard D Avila, Imran Ahmad
Architecting AI Software Systems provides a definitive guide to building AI-enabled systems, emphasizing the balance between AI’s capabilities and traditional software architecture principles.As AI technologies gain widespread acceptance and are increasingly expected in future applications, this book provides architects and developers with the essential knowledge to stay competitive. It introduces a structured approach to mastering the complexities of AI integration, covering key architectural concepts and processes critical to building scalable and robust AI systems while minimizing development and maintenance risks. The book guides readers on a progressive journey, using real-world examples and hands-on exercises to deepen comprehension. It also includes the architecture of a fictional AI-enabled system as a learning tool. You will engage with exercises designed to reinforce your understanding and apply practical insights, leading to the development of key architectural products that support AI systems. This is an essential resource for architects seeking to mitigate risks and master the complexities of AI-enabled system development.By the end of the book, readers will be equipped with patterns, strategies and concepts necessary to architect AI-enabled systems across various domains.
Richard D Avila, Imran Ahmad
Architecting AI Software Systems provides a definitive guide to building AI-enabled systems, emphasizing the balance between AI’s capabilities and traditional software architecture principles.As AI technologies gain widespread acceptance and are increasingly expected in future applications, this book provides architects and developers with the essential knowledge to stay competitive. It introduces a structured approach to mastering the complexities of AI integration, covering key architectural concepts and processes critical to building scalable and robust AI systems while minimizing development and maintenance risks. The book guides readers on a progressive journey, using real-world examples and hands-on exercises to deepen comprehension. It also includes the architecture of a fictional AI-enabled system as a learning tool. You will engage with exercises designed to reinforce your understanding and apply practical insights, leading to the development of key architectural products that support AI systems. This is an essential resource for architects seeking to mitigate risks and master the complexities of AI-enabled system development.By the end of the book, readers will be equipped with patterns, strategies and concepts necessary to architect AI-enabled systems across various domains.
Lars Malmqvist
Written for Salesforce architects who want quickly implementable AI solutions for their business challenges, Architecting AI Solutions on Salesforce is a shortcut to understanding Salesforce Einstein’s full capabilities – and using them.To illustrate the full technical benefits of Salesforce’s own AI solutions and components, this book will take you through a case study of a fictional company beginning to adopt AI in its Salesforce ecosystem. As you progress, you'll learn how to configure and extend the out-of-the-box features on various Salesforce clouds, their pros, cons, and limitations. You'll also discover how to extend these features using on- and off-platform choices and how to make the best architectural choices when designing custom solutions. Later, you'll advance to integrating third-party AI services such as the Google Translation API, Microsoft Cognitive Services, and Amazon SageMaker on top of your existing solutions. This isn’t a beginners’ Salesforce book, but a comprehensive overview with practical examples that will also take you through key architectural decisions and trade-offs that may impact the design choices you make.By the end of this book, you'll be able to use Salesforce to design powerful tailor-made solutions for your customers with confidence.
Marcotte, Nick Cosentino
This unique ASP.NET Core book will fill in the gaps in your REST API and backend designs. Learn how to build robust, maintainable, and flexible apps using Gang of Four (GoF) design patterns and modern architectural principles. This new edition is updated for .NET 8 and focuses exclusively on the backend, with new content on REST APIs, the REPR pattern, and building modular monoliths.You’ll start by covering foundational concepts like REST, the SOLID principles, Minimal APIs, dependency injection in .NET, and other ASP.NET Core 8 mechanisms. Then, you’ll learn to develop components using design patterns, including many from the GoF. Finally, you’ll explore organizing your application code with patterns that vary from layers to feature-oriented vertical slice designs, covering CQS and a deep dive into microservices along the way. A brand-new e-commerce project at the end of the book will tie it all together.This how-to guide will teach you how to assemble your own APIs from building blocks, to suit whatever real-world requirements you may have.
Erol Kavas
Infrastructure as code (IaC) and Terraform have become essential tools for managing cloud infrastructure and automating deployment processes. Mastering Terraform on AWS presents a step-by-step approach on how to master these tools and build a secure and scalable AWS infrastructure. The book starts with an introduction to patterns and anti-patterns of IaC and Terraform, explaining the common mistakes and pitfalls you must avoid. You’ll then learn about the importance of planning and designing infrastructure projects in AWS and making informed decisions for projects in AWS Terraform. You’ll find out how to implement Terraform in your projects and deploy serverless projects. Next, you’ll be able to deploy containers in AWS with Terraform, exploring the best practices for Terraform IaC projects. You’ll understand how you can leverage Terraform for enterprises, build Git workflows for IaC and Terraform projects, and automate deployment of Terraform projects. The last set of chapters will teach you how to govern AWS with Terraform and build a secure infrastructure. Finally, you’ll discover how to achieve a perfect AWS infrastructure with Terraform. By the end of this book, you’ll have gained a comprehensive understanding of the various aspects of Terraform and IaC, along with the knowledge required to build, manage, and deploy complex infrastructures on AWS.
Kevin L. Jackson, Scott Goessling
Cloud adoption is a core component of digitaltransformation. Scaling the IT environment,making it resilient, and reducing costs arewhat organizations want. Architecting CloudComputing Solutions presents and explainscritical cloud solution design considerationsand technology decisions required tobe made for deploying the right cloudservice and deployment models,based on your business andtechnology service requirements.This book starts with the fundamentalsof cloud computing and its architecturalconcepts. It then walks you throughcloud service models (IaaS, PaaS, andSaaS), deployment models (public,private, community, and hybrid)and implementation options(enterprise, MSP, and CSP) to explainand describe the key considerations andchallenges organizations face during cloudmigration. Later, this book delves into how toleverage DevOps, Cloud-Native, and serverlessarchitectures in your cloud environmentand presents industry best practices forscaling your cloud environment. Finally,this book addresses in depth how tomanage essential cloud technologyservice components, such as data storage,security controls, and disaster recovery.By the end of this book, you will havemastered all the design considerations andoperational trades required to adopt cloudservices, no matter which cloud serviceprovider you choose.
Kevin L. Jackson, Scott Goessling
Cloud adoption is a core component of digitaltransformation. Scaling the IT environment,making it resilient, and reducing costs arewhat organizations want. Architecting CloudComputing Solutions presents and explainscritical cloud solution design considerationsand technology decisions required tobe made for deploying the right cloudservice and deployment models,based on your business andtechnology service requirements.This book starts with the fundamentalsof cloud computing and its architecturalconcepts. It then walks you throughcloud service models (IaaS, PaaS, andSaaS), deployment models (public,private, community, and hybrid)and implementation options(enterprise, MSP, and CSP) to explainand describe the key considerations andchallenges organizations face during cloudmigration. Later, this book delves into how toleverage DevOps, Cloud-Native, and serverlessarchitectures in your cloud environmentand presents industry best practices forscaling your cloud environment. Finally,this book addresses in depth how tomanage essential cloud technologyservice components, such as data storage,security controls, and disaster recovery.By the end of this book, you will havemastered all the design considerations andoperational trades required to adopt cloudservices, no matter which cloud serviceprovider you choose.