Sztuczna inteligencja
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.
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.
(Nie)etyczna AI. Jak programować odpowiedzialnie w erze sztucznej inteligencji
Paweł Półtorak
Technologia - wspaniała i groźna zarazem. Także w Twoich rękach Czy rozwój sztucznej inteligencji budzi w Tobie mieszane uczucia? Z jednej strony fascynuje potencjałem, z drugiej - rodzi wątpliwości? Autor książki, doświadczony strateg i doradca w obszarze nowych technologii, stawia się w pozycji sygnalisty, by zwrócić uwagę na obszary, w których rozwój AI może pójść w niebezpiecznym kierunku. Choć dostrzega ogromne możliwości, jakie niesie sztuczna inteligencja - od transformacji biznesów po poprawę jakości życia - nie odwraca wzroku od ciemnych stron tej technologii. Znajdziesz tu analizę ryzyka związanego z AI, takiego jak brak transparentności, niewłaściwe zarządzanie danymi i potencjalne manipulacje, które mogą wpływać na społeczeństwo w skali globalnej. Celem książki nie jest jedynie wywołanie refleksji nad tymi zagrożeniami, ale przede wszystkim pokazanie, jak im zapobiegać. W pierwszej części autor zwraca uwagę na niebezpieczeństwa, jakie wiążą się z nieumiejętnym, nieprzemyślanym, a czasami także nieetycznym podejściem do projektowania technologii i zastosowań AI. W drugiej proponuje zestaw praktycznych wskazówek dla każdego, kto pracuje nad rozwojem sztucznej inteligencji i pragnie robić to w sposób etyczny. Ta książka to nie tylko ostrzeżenie przed zagrożeniami związanymi z AI, ale przede wszystkim drogowskaz dla twórców nowoczesnych technologii.
Lovisa Stenbäcken Stjernlöf, HenkJan de Vries
IAM, short for identity and access management, is a set of policies and technologies for ensuring the security of an organization through careful role and access assignment for users and devices. With this book, you’ll get up and running with Okta, an identity and access management (IAM) service that you can use for both employees and customers.Once you’ve understood how Okta can be used as an IAM platform, you’ll learn about the Universal Directory, which covers how to integrate other directories and applications and set up groups and policies. As you make progress, the book explores Okta’s single sign-on (SSO) feature and multifactor authentication (MFA) solutions. Finally, you will delve into API access management and discover how you can leverage Advanced Server Access for your cloud servers and Okta Access Gateway for your on-premises applications.By the end of this Okta book, you’ll have learned how to implement Okta to enhance your organization's security and be able to use this book as a reference guide for the Okta certification exam.
Henry Habib, Sam McKay, Paul Siegel
As artificial intelligence continues to reshape industries with OpenAI at the forefront of AI research, knowing how to create innovative applications such as chatbots, virtual assistants, content generators, and productivity enhancers is a game-changer. This book takes a practical, recipe-based approach to unlocking the power of OpenAI API to build high-performance intelligent applications in diverse industries and seamlessly integrate ChatGPT in your workflows to increase productivity.You’ll begin with the OpenAI API fundamentals, covering setup, authentication, and key parameters, and quickly progress to the different elements of the OpenAI API. Once you’ve learned how to use it effectively and tweak parameters for better results, you’ll follow advanced recipes for enhancing user experience and refining outputs. The book guides your transition from development to live application deployment, setting up the API for public use and application backend. Further, you’ll discover step-by-step recipes for building knowledge-based assistants and multi-model applications tailored to your specific needs.By the end of this book, you’ll have worked through recipes involving various OpenAI API endpoints and built a variety of intelligent applications, ready to apply this experience to building AI-powered solutions of your own.
Henry Habib
Firma OpenAI pozostaje niekwestionowanym liderem badań nad sztuczną inteligencją. Dzięki udostępnianym przez nią rozwiązaniom tworzenie innowacyjnych aplikacji, takich jak czatboty, wirtualne asystenty, generatory treści i narzędzia zwiększające produktywność, stało się o wiele prostsze. Bezsprzecznie powszechna dostępność technologii AI zmienia zasady gry! Receptury zawarte w tym zbiorze ułatwią Ci budowę szerokiej gamy inteligentnych aplikacji. Zaczniesz od podstaw OpenAI API - konfiguracji, uwierzytelniania i kluczowych parametrów - po czym szybko przejdziesz do nauki korzystania z najważniejszych elementów API. Następnie przyjdzie czas na zaawansowane receptury, dzięki którym poprawisz wrażenia użytkownika i dopracujesz dane wyjściowe. Dowiesz się, jak wdrażać aplikacje i przygotować je do publicznego użytku. Nauczysz się również budowania inteligentnych asystentów opartych na specjalistycznej wiedzy, a także aplikacji multimodalnych dostosowanych do Twoich specyficznych potrzeb. W książce: podstawy interfejsu OpenAI API, jego możliwości i ograniczenia konfiguracja OpenAI API krok po kroku zaawansowane funkcje, w tym komunikat systemowy i dostrajanie integracja OpenAI API z istniejącymi aplikacjami i procesami projektowanie aplikacji wykorzystujących w pełni możliwości OpenAI API Postęp technologii polega na dostosowaniu jej tak, abyśmy nawet jej nie zauważali i by mogła stać się częścią codziennego życia! Bill Gates
Joseph Howse, Steven Puttemans, Utkarsh Sinha
Computer vision is becoming accessible to a large audience of software developers who can leverage mature libraries such as OpenCV. However, as they move beyond their first experiments in computer vision, developers may struggle to ensure that their solutions are sufficiently well optimized, well trained, robust, and adaptive in real-world conditions. With sufficient knowledge of OpenCV, these developers will have enough confidence to go about creating projects in the field of computer vision.This book will help you tackle increasingly challenging computer vision problems that you may face in your careers. It makes use of OpenCV 3 to work around some interesting projects. Inside these pages, you will find practical and innovative approaches that are battle-tested in the authors’ industry experience and research. Each chapter covers the theory and practice of multiple complementary approaches so that you will be able to choose wisely in your future projects. You will also gain insights into the architecture and algorithms that underpin OpenCV’s functionality.We begin by taking a critical look at inputs in order to decide which kinds of light, cameras, lenses, and image formats are best suited to a given purpose. We proceed to consider the finer aspects of computational photography as we build an automated camera to assist nature photographers. You will gain a deep understanding of some of the most widely applicable and reliable techniques in object detection, feature selection, tracking, and even biometric recognition. We will also build Android projects in which we explore the complexities of camera motion: first in panoramic image stitching and then in video stabilization.By the end of the book, you will have a much richer understanding of imaging, motion, machine learning, and the architecture of computer vision libraries and applications!
Robert Laganiere
OpenCV 3 Computer Vision Application Programming Cookbook is appropriate for novice C++ programmers who want to learn how to use the OpenCV library to build computer vision applications. It is also suitable for professional software developers wishing to be introduced to the concepts of computer vision programming. It can also be used as a companion book in a university-level computer vision courses. It constitutes an excellent reference for graduate students and researchers in image processing and computer vision.