Sztuczna inteligencja
Aleksander Molak, Ajit Jaokar
Causal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that elude a purely statistical mindset. Causal Inference and Discovery in Python helps you unlock the potential of causality.You’ll start with basic motivations behind causal thinking and a comprehensive introduction to Pearlian causal concepts, such as structural causal models, interventions, counterfactuals, and more. Each concept is accompanied by a theoretical explanation and a set of practical exercises with Python code. Next, you’ll dive into the world of causal effect estimation, consistently progressing towards modern machine learning methods. Step-by-step, you’ll discover Python causal ecosystem and harness the power of cutting-edge algorithms. You’ll further explore the mechanics of how “causes leave traces” and compare the main families of causal discovery algorithms. The final chapter gives you a broad outlook into the future of causal AI where we examine challenges and opportunities and provide you with a comprehensive list of resources to learn more.By the end of this book, you will be able to build your own models for causal inference and discovery using statistical and machine learning techniques as well as perform basic project assessment.
Dr. Scott Dell, Dr. Mfon Akpan
In the fast-paced AI world, accounting professionals are increasingly challenged by the complexities of AI. Many struggle to integrate these advanced tools into their workflows, leading to a sense of overwhelm. ChatGPT for Accounting bridges this gap by not only simplifying AI concepts but also offering practical insights for its application in various accounting domains.This book takes you from the foundational principles of Generative Artificial Intelligence (GAI) to its practical applications in audits, tax planning, practice management, fraud examination, financial analysis, and beyond. Each chapter equips you with essential skills, showing you how AI can revolutionize internal control systems, enhance recruitment processes, streamline marketing plans, optimize tax strategies, and boost efficiency in audits. You’ll then advance to exploring the role of AI in forensic accounting, financial analysis, managerial accounting, and corporate governance, while also addressing ethical and security implications.Concluding with a reflective outlook on the promises and challenges of AI, you’ll gain a holistic view of the future of accounting. By the end of this book, you’ll be equipped with the knowledge to harness the power of AI effectively and ethically, transforming your accounting practice and staying ahead in the ever-evolving landscape.
Andy Forbes, Philip Safir, Joseph Kubon, Francisco...
Authored by a team of Salesforce masters with exemplary IT background, ChatGPT for Salesforce Development helps you learn about the intricacies of Salesforce design, configuration, coding, and testing, demonstrating how ChatGPT can simplify complex setups and enhance project team efficiency.With this book, you’ll unlock the effective use of ChatGPT for crafting user stories that align seamlessly with project goals, learn how to design and implement Salesforce flows, and quickly write clear, comprehensive, and high-quality project documentation. You’ll leverage ChatGPT to write new Apex code, decipher existing code, and explore the development of web services and callouts. This book covers everything from trigger creation to the development of Lightning Web Components (LWC), highlighting how these can accelerate the development process. Applying ChatGPT's debugging capabilities, you’ll swiftly identify and resolve Salesforce issues to uphold the integrity and performance of your Salesforce applications.By the end of this book, you’ll be adept at integrating ChatGPT at every stage of Salesforce project delivery, from initial configuration to final testing.
Adrian Thompson
ChatGPT for Conversational AI and Chatbots is a definitive resource for exploring conversational AI, ChatGPT, and large language models.This book introduces the fundamentals of ChatGPT and conversational AI automation. You’ll explore the application of ChatGPT in conversation design, the use of ChatGPT as a tool to create conversational experiences, and a range of other practical applications. As you progress, you’ll delve into LangChain, a dynamic framework for LLMs, covering topics such as prompt engineering, chatbot memory, using vector stores, and validating responses. Additionally, you’ll learn about creating and using LLM-enabling tools, monitoring and fine tuning, LangChain UI tools such as LangFlow, and the LangChain ecosystem. You’ll also cover popular use cases, such as using ChatGPT in conjunction with your own data. Later, the book focuses on creating a ChatGPT-powered chatbot that can comprehend and respond to queries directly from your unique data sources. The book then guides you through building chatbot UIs with ChatGPT API and some of the tools and best practices available.By the end of this book, you’ll be able to confidently leverage ChatGPT technologies to build conversational AI solutions.
Clint Bodungen, Aaron Crow
Are you ready to unleash the potential of AI-driven cybersecurity? This cookbook takes you on a journey toward enhancing your cybersecurity skills, whether you’re a novice or a seasoned professional. By leveraging cutting-edge generative AI and large language models such as ChatGPT, you'll gain a competitive advantage in the ever-evolving cybersecurity landscape.ChatGPT for Cybersecurity Cookbook shows you how to automate and optimize various cybersecurity tasks, including penetration testing, vulnerability assessments, risk assessment, and threat detection. Each recipe demonstrates step by step how to utilize ChatGPT and the OpenAI API to generate complex commands, write code, and even create complete tools. You’ll discover how AI-powered cybersecurity can revolutionize your approach to security, providing you with new strategies and techniques for tackling challenges. As you progress, you’ll dive into detailed recipes covering attack vector automation, vulnerability scanning, GPT-assisted code analysis, and more. By learning to harness the power of generative AI, you'll not only expand your skillset but also increase your efficiency.By the end of this cybersecurity book, you’ll have the confidence and knowledge you need to stay ahead of the curve, mastering the latest generative AI tools and techniques in cybersecurity.
ChatGPT. Podstawy i proste zastosowania
Filip Sala, Marzena Sala-Tefelska, Maksymilian Bujok
Twój nowy, nad wyraz inteligentny współpracownik ChatGPT, czyli flagowy produkt firmy OpenAI, jest dziś na ustach wszystkich. Przyglądamy się dotychczasowym zastosowaniom sztucznej inteligencji, ale nasze myśli najbardziej zaprzątają przewidywania co do jej przyszłości. Autorzy udowadniają, że nie mamy się czego obawiać. Co więcej, pokazują, że najlepszym sposobem na pokonanie strachu przed nieznanym jest zrozumienie, czego się boimy. A możemy to osiągnąć dzięki praktycznym wskazówkom udzielonym w tej książce. Współpraca z ChatGPT wymaga pewnego przygotowania. Niewątpliwą zaletą tej technologii jest to, że można się z nią porozumieć za pomocą języka naturalnego ― takiego, jakim komunikujemy się ze sobą na co dzień. Rzecz w tym, by nauczyć się w odpowiedni sposób zadawać pytania i wydawać polecenia, czyli tworzyć tak zwane prompty. W trakcie lektury prześledzisz różne metody tworzenia zapytań i poznasz konkretne przykłady ich zastosowania. Dowiesz się między innymi, jak pracować z tekstem, grafiką i analizą danych, a także jak skorzystać z ChatGPT do celów dydaktycznych. Zrozumiesz również, jak sztuczna inteligencja może Cię wesprzeć w programowaniu i projektowaniu. Dzięki temu będziesz w stanie osiągnąć wszystkie cele, jakie sobie wyznaczasz ― i to zarówno w życiu osobistym, jak i zawodowym. Już dziś rozpocznij przygodę z ChatGPT! Książka jest przeznaczona przede wszystkim dla osób początkujących i tych, które ze sztuczną inteligencją nie miały dotychczas do czynienia. Zachęcamy również do odwiedzenia kanału naukowego Sala Science prowadzonego przez autorów na platformie YouTube.
Oliver Theobald
The course embarks on an enlightening journey through the world of ChatGPT, starting from the very basics of understanding what ChatGPT is, to delving deep into the mechanics of crafting precision prompts that unlock its full potential. From the outset, you'll be introduced to the foundational elements that make ChatGPT an indispensable tool for a wide range of applications, setting the stage for a comprehensive exploration of its capabilities.As we progress, the course meticulously unfolds the layers of prompt writing techniques, priming strategies, and training methodologies that are designed to enhance your interaction with AI. You'll learn how to craft prompts for common use cases, navigate the nuances of content creation, translation tasks, and personalized tutoring, all while leveraging ChatGPT's advanced AI art capabilities.The course culminates by focusing on practical applications and exploring advanced prompt training and role prompting techniques. This final stretch is designed to solidify your understanding and empower you with the confidence to employ ChatGPT across various scenarios, from professional content writing to creative explorations.
ChatGPT w życiu, pracy i biznesie
Marcin Stokłosa
ChatGPT to nie tylko chatbot - to osobisty asystent, organizator, edytor i pomysłodawca w jednym. Ten e-book pokazuje krok po kroku, jak korzystać z jego możliwości w praktyce: w codziennym życiu, zawodowo oraz w rozwoju własnych projektów. Znajdziesz tu ponad 50 gotowych promptów, checklisty, narzędzia, ćwiczenia i historie z życia. Niezależnie od tego, czy dopiero zaczynasz, czy już testujesz AI - ten przewodnik jest dla Ciebie. Marcin Stokłosa Pasjonat technologii, entuzjasta rozwiązań smart home i autor praktycznych poradników dla każdego, kto chce lepiej wykorzystywać nowoczesne narzędzia w życiu codziennym i zawodowym. Od ponad 10 lat mieszka w Niemczech, gdzie łączy pracę zawodową z własnymi projektami online. Tworzy treści edukacyjne, które tłumaczą złożone tematy prostym językiem - bez zbędnego żargonu i teorii. Jego celem jest pomagać zwykłym ludziom skutecznie korzystać z potencjału sztucznej inteligencji - w pracy, nauce, biznesie i domowych obowiązkach. W swoich materiałach stawia na konkret, klarowność i natychmiastową użyteczność.
CHROŃ I ROZWIJAJ BIZNES - CYBER AI Część 1 Wykorzystanie AI w bezpieczeństwie organizacji
Dariusz Gołębiowski
Masz firmę, fundację, albo inną organizację, którą chcesz ochronić przed cyberzagrożeniami? Świetnie, bo właśnie trzymasz wirtualną broń do walki z cyfrowymi złoczyńcami! Pierwsza część serii "CHROŃ I ROZWIJAJ BIZNES - CYBER AI" to Twoje kompendium wiedzy o tym, jak nie tylko wywinąć się z rąk hakerów, ale też sprytnie wdrożyć sztuczną inteligencję, która pomoże Ci spać spokojnie... no, przynajmniej dopóki AI nie zacznie przejmować kontroli nad światem. 😉 W tej książce dowiesz się, dlaczego malware to coś więcej niż problem komputera wujka Janka, jak unikać pułapek phishingowych, które są bardziej podstępne niż zaproszenie na "darmową pizzę", oraz dlaczego dyrektywa NIS 2 nie jest tylko kolejnym nudnym prawniczym dokumentem, który gdzieś tam podpisano. A teraz najlepsza część: sztuczna inteligencja (tak, ta od filmów sci-fi!) może być Twoim najlepszym przyjacielem w walce z zagrożeniami. Dzięki AI Twój system zabezpieczeń będzie niczym Sherlock Holmes, który znajdzie każdą podejrzaną aktywność, zanim jeszcze pomyślisz o kawie. W książce znajdziesz konkretne przykłady, jak AI może ochronić Twoje dane, monitorować pracowników (bez robienia z tego kolejnego odcinka live-streaam badziewnych seriali dla samotnych ludzi) i automatyzować reakcje na zagrożenia. Jeśli myślisz, że to koniec... to niespodzianka! Druga część serii, zaplanowana na przyszły rok, będzie o tym, jak sztuczna inteligencja nie tylko ochroni Twoją organizację, ale także pomoże Ci ją rozwijać - kto wie, może nawet stworzy dla Ciebie plan na podbój świata (w granicach prawa, oczywiście). Nie przegap okazji, żeby zabezpieczyć swój biznes przed zagrożeniami, które krążą w sieci szybciej niż memy z kotami. Zrób to z uśmiechem i nutą technologicznej magii!
CHROŃ I ROZWIJAJ BIZNES CYBER AI Księga 1 Sztuczna Inteligencja
Gołębiowski Dariusz
Sztuczna inteligencja nie jest przyszłością. Jest teraźniejszością - pytanie brzmi: czy Twoja firma jest na nią gotowa? Ten ebook to praktyczny przewodnik po świecie AI dla właścicieli firm, zarządów, dyrektorów i liderów, którzy: nie chcą "bawić się technologią", nie mają czasu na marketingowy bełkot, chcą konkretnie wiedzieć: co wdrożyć, po co, jak i gdzie są granice bezpieczeństwa. Nie znajdziesz tu futurystycznych wizji ani skomplikowanych algorytmów. Znajdziesz za to AI pokazane "poswojsku" - z perspektywy decyzji, ryzyka, pieniędzy i odpowiedzialności. 🔍 Czego się dowiesz? gdzie AI realnie pomaga firmom (zarządzanie, cyberbezpieczeństwo, marketing, sprzedaż, usługi), gdzie AI może zaszkodzić, jeśli zostanie wdrożona bez refleksji, jak oddzielić modne narzędzia od faktycznej wartości biznesowej, jakie obowiązki prawne wynikają z AI Act i co to oznacza dla MŚP, jak wdrażać AI bezpiecznie, odpowiedzialnie i zgodnie z prawem, jak przygotować organizację krok po kroku - bez chaosu i kosztownych błędów. 🧭 Dla kogo jest ta książka? dla właścicieli małych i średnich firm, dla prezesów, dyrektorów, menedżerów, dla osób odpowiedzialnych za bezpieczeństwo, IT, dane lub rozwój, dla tych, którzy chcą rozumieć AI, a nie tylko jej używać. ✅ Co ją wyróżnia? konkretne przykłady zastosowań, jasny język, bez technicznego żargonu, aktualne prawo (AI Act), checklisty AI-READY i AI-SAFE, mini-kompas decyzyjny dla zarządu, nacisk na człowieka, odpowiedzialność i zdrowy rozsądek. To nie jest książka o tym, jak "zachwycić się AI". To książka o tym, jak używać AI mądrze - i nie żałować tej decyzji za rok lub dwa. ⭐ Recenzja czytelnika - Pan Kazimierz, Prezes i Właściciel firmy usługowej "W końcu ktoś napisał o AI normalnie." Prowadzę niewielką firmę usługową od ponad 20 lat. O sztucznej inteligencji słyszałem wszędzie - w mediach, na konferencjach, od handlowców. Problem był jeden: nikt nie potrafił mi jasno powiedzieć, czy ja w ogóle jej potrzebuję i gdzie są zagrożenia. Ta książka trafiła do mnie w idealnym momencie. Autor nie próbuje mnie przekonać, że "muszę mieć AI, bo wszyscy mają". Zamiast tego pokazuje: gdzie AI ma sens, gdzie lepiej się zatrzymać, i co najważniejsze - kto za to wszystko odpowiada. Bardzo doceniam podejście zarządcze i prawne. AI Act był dla mnie kompletnie nieczytelny - tutaj dostałem konkretne wyjaśnienie, bez straszenia i bez bagatelizowania tematu. Checklisty na końcu? Złoto. Usiadłem z nimi razem z kierownikiem i w godzinę mieliśmy jasny obraz: co możemy zrobić teraz, a czego na razie nie ruszamy. To nie jest książka dla informatyków. To książka dla ludzi, którzy podejmują decyzje i biorą za nie odpowiedzialność. Polecam każdemu właścicielowi firmy, który chce spać spokojnie, a nie gonić za modą. - Kazimierz, Prezes i Właściciel firmy usługowej
Angelica Lo Duca
This book provides concepts and practical use cases which can be used to quickly build, monitor, and optimize data science projects. Using Comet, you will learn how to manage almost every step of the data science process from data collection through to creating, deploying, and monitoring a machine learning model.The book starts by explaining the features of Comet, along with exploratory data analysis and model evaluation in Comet. You’ll see how Comet gives you the freedom to choose from a selection of programming languages, depending on which is best suited to your needs. Next, you will focus on workspaces, projects, experiments, and models. You will also learn how to build a narrative from your data, using the features provided by Comet. Later, you will review the basic concepts behind DevOps and how to extend the GitLab DevOps platform with Comet, further enhancing your ability to deploy your data science projects. Finally, you will cover various use cases of Comet in machine learning, NLP, deep learning, and time series analysis, gaining hands-on experience with some of the most interesting and valuable data science techniques available.By the end of this book, you will be able to confidently build data science pipelines according to bespoke specifications and manage them through Comet.
Denis Rothman
Generative AI is powerful, yet often unpredictable. This guide shows you how to turn that unpredictability into reliability by thinking beyond prompts and approaching AI like an architect. At its core is the Context Engine, a glass-box, multi-agent system you’ll learn to design and apply across real-world scenarios.Written by an AI guru and author of various cutting-edge AI books, this book takes you on a hands-on journey from the foundations of context design to building a fully operational Context Engine. Instead of relying on brittle prompts that give only simple instructions, you’ll begin with semantic blueprints that map goals and roles with precision, then orchestrate specialized agents using the Model Context Protocol. As the engine evolves, you’ll integrate memory and high-fidelity retrieval with citations, implement safeguards against data poisoning and prompt injection, and enforce moderation to keep outputs aligned with policy. You’ll also harden the system into a resilient architecture, then see it pivot across domains, from legal compliance to strategic marketing, proving its domain independence.By the end of this book, you’ll be equipped with the skills to engineer an adaptable, verifiable architecture you can repurpose across domains and deploy with confidence.*Email sign-up and proof of purchase required
Dr. Alex Antic, John K. Thompson
A Gartner prediction in 2018 led to numerous articles stating that 85% of AI and machine learning projects fail to deliver.” Although it's unclear whether a mass extinction event occurred for AI implementations at the end of 2022, the question remains: how can I ensure that my project delivers value and doesn't become a statistic?The demand for data scientists has only grown since 2015, when they were dubbed the new “rock stars” of business. But how can you become a data science rock star? As a new senior data leader, how can you build and manage a productive team? And what is the path to becoming a chief data officer?Creators of Intelligence is a collection of in-depth, one-on-one interviews where Dr. Alex Antic, a recognized data science leader, explores the answers to these questions and more with some of the world's leading data science leaders and CDOs.Interviews with: Cortnie Abercrombie, Edward Santow, Kshira Saagar, Charles Martin, Petar Veličković, Kathleen Maley, Kirk Borne, Nikolaj Van Omme, Jason Tamara Widjaja, Jon Whittle, Althea Davis, Igor Halperin, Christina Stathopoulos, Angshuman Ghosh, Maria Milosavljevic, Dr. Meri Rosich, Dat Tran, and Stephane Doyen.
CSS3 and SVG with Meta AI. AI-Driven CSS3 and SVG Design Techniques for Modern Web Solutions
Mercury Learning and Information, Oswald Campesato
This book introduces the innovative integration of CSS3 and SVG with generative AI tools, providing a foundation for modern web design. Readers begin by exploring the basics of generative AI and prompt engineering, gaining insights into how these technologies influence visual storytelling and creativity in web design.Progressing through the chapters, the book covers essential CSS3 concepts, including 3D animations and dynamic styling, before delving into advanced SVG techniques for creating scalable and responsive vector graphics. With practical examples, readers learn to merge CSS3 and SVG, enabling the development of seamless AI-enhanced animations and graphics tailored to modern design needs. The integration of Meta AI is highlighted, showcasing its role in enhancing workflows and achieving innovative solutions.By the end, readers will have gained the skills to create cutting-edge, scalable, and visually engaging web designs. The book equips developers with the knowledge and tools to incorporate AI-driven enhancements into their projects, ensuring designs remain both innovative and practical for real-world applications.
Greg Deckler
DAX provides an extra edge by extracting key information from the data that is already present in your model. Filled with examples of practical, real-world calculations geared toward business metrics and key performance indicators, this cookbook features solutions that you can apply for your own business analysis needs.You'll learn to write various DAX expressions and functions to understand how DAX queries work. The book also covers sections on dates, time, and duration to help you deal with working days, time zones, and shifts. You'll then discover how to manipulate text and numbers to create dynamic titles and ranks, and deal with measure totals. Later, you'll explore common business metrics for finance, customers, employees, and projects. The book will also show you how to implement common industry metrics such as days of supply, mean time between failure, order cycle time and overall equipment effectiveness. In the concluding chapters, you'll learn to apply statistical formulas for covariance, kurtosis, and skewness. Finally, you'll explore advanced DAX patterns for interpolation, inverse aggregators, inverse slicers, and even forecasting with a deseasonalized correlation coefficient.By the end of this book, you'll have the skills you need to use DAX's functionality and flexibility in business intelligence and data analytics.
Cher Simon
Despite promising advances, the opaque nature of deep learning models makes it difficult to interpret them, which is a drawback in terms of their practical deployment and regulatory compliance.Deep Learning and XAI Techniques for Anomaly Detection shows you state-of-the-art methods that’ll help you to understand and address these challenges. By leveraging the Explainable AI (XAI) and deep learning techniques described in this book, you’ll discover how to successfully extract business-critical insights while ensuring fair and ethical analysis.This practical guide will provide you with tools and best practices to achieve transparency and interpretability with deep learning models, ultimately establishing trust in your anomaly detection applications. Throughout the chapters, you’ll get equipped with XAI and anomaly detection knowledge that’ll enable you to embark on a series of real-world projects. Whether you are building computer vision, natural language processing, or time series models, you’ll learn how to quantify and assess their explainability.By the end of this deep learning book, you’ll be able to build a variety of deep learning XAI models and perform validation to assess their explainability.
Upendra Kumar Devisetty
Deep learning has shown remarkable promise in the field of genomics; however, there is a lack of a skilled deep learning workforce in this discipline. This book will help researchers and data scientists to stand out from the rest of the crowd and solve real-world problems in genomics by developing the necessary skill set. Starting with an introduction to the essential concepts, this book highlights the power of deep learning in handling big data in genomics. First, you’ll learn about conventional genomics analysis, then transition to state-of-the-art machine learning-based genomics applications, and finally dive into deep learning approaches for genomics. The book covers all of the important deep learning algorithms commonly used by the research community and goes into the details of what they are, how they work, and their practical applications in genomics. The book dedicates an entire section to operationalizing deep learning models, which will provide the necessary hands-on tutorials for researchers and any deep learning practitioners to build, tune, interpret, deploy, evaluate, and monitor deep learning models from genomics big data sets.By the end of this book, you’ll have learned about the challenges, best practices, and pitfalls of deep learning for genomics.
Vitor Cerqueira, Luís Roque
Most organizations exhibit a time-dependent structure in their processes, including fields such as finance. By leveraging time series analysis and forecasting, these organizations can make informed decisions and optimize their performance. Accurate forecasts help reduce uncertainty and enable better planning of operations. Unlike traditional approaches to forecasting, deep learning can process large amounts of data and help derive complex patterns. Despite its increasing relevance, getting the most out of deep learning requires significant technical expertise.This book guides you through applying deep learning to time series data with the help of easy-to-follow code recipes. You’ll cover time series problems, such as forecasting, anomaly detection, and classification. This deep learning book will also show you how to solve these problems using different deep neural network architectures, including convolutional neural networks (CNNs) or transformers. As you progress, you’ll use PyTorch, a popular deep learning framework based on Python to build production-ready prediction solutions.By the end of this book, you'll have learned how to solve different time series tasks with deep learning using the PyTorch ecosystem.
Deep Learning from the Basics. Python and Deep Learning: Theory and Implementation
Koki Saitoh, Shigeo Yushita
Deep learning is rapidly becoming the most preferred way of solving data problems. This is thanks, in part, to its huge variety of mathematical algorithms and their ability to find patterns that are otherwise invisible to us.Deep Learning from the Basics begins with a fast-paced introduction to deep learning with Python, its definition, characteristics, and applications. You’ll learn how to use the Python interpreter and the script files in your applications, and utilize NumPy and Matplotlib in your deep learning models. As you progress through the book, you’ll discover backpropagation—an efficient way to calculate the gradients of weight parameters—and study multilayer perceptrons and their limitations, before, finally, implementing a three-layer neural network and calculating multidimensional arrays.By the end of the book, you’ll have the knowledge to apply the relevant technologies in deep learning.
Alan M. F. Souza, Fabio M. Soares,...
Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognitionStarting with an introduction to basic machine learning algorithms, this course takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. This course helps you solve challenging problems in image processing, speech recognition, language modeling. You will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text. You will also work with examples such as weather forecasting, disease diagnosis, customer profiling, generalization, extreme machine learning and more. By the end of this course, you will have all the knowledge you need to perform deep learning on your system with varying complexity levels, to apply them to your daily work.The course provides you with highly practical content explaining deep learning with Java, from the following Packt books:1. Java Deep Learning Essentials 2. Machine Learning in Java3. Neural Network Programming with Java, Second Edition
Deep Learning with C++. Design and deploy neural networks using CUDA for high-performance AI in C++
Bill Chen, Vikash Gupta
Deep learning systems often struggle to meet performance demands in real-time and production environments. This book shows you how to build high-performance deep learning systems in C++, enabling efficient and scalable artificial intelligence (AI) in resource-constrained environments where performance matters.You’ll start by setting up a complete C++ deep learning environment and implementing core neural networks from scratch. As you progress, you’ll build advanced architectures, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory Networks (LSTMs), Generative Adversarial Networks (GANs), and Transformers, using C++, CUDA, and PyTorch’s C++ API. The book then focuses on model quantization and compression. It will guide you through the model deployment process in production with robust monitoring and explainability. You’ll also explore distributed training and techniques for real-time inference in performance-critical domains.By the end of this book, you’ll be able to design, optimize, and deploy deep learning systems in C++ that are production-ready, scalable, and efficient across multiple industries.*Email sign-up and proof of purchase required
Andy Peng, Alex Strick van Linschoten, Duarte...
Learn how to build, fine-tune, and deploy AI systems using DeepSeek, one of the most influential open-source large language models available today. This book guides you through real-world DeepSeek applications—from understanding its core architecture and training foundations to developing reasoning agents and deploying production-ready systems.Starting with a concise synthesis of DeepSeek's research, breakthroughs, and open-source philosophy, you’ll progress to hands-on projects including prompt engineering, workflow design, and rationale distillation. Through detailed case studies—ranging from document understanding to legal clause analysis—you’ll see how to use DeepSeek in high-value GenAI scenarios.You’ll also learn to build sophisticated agent workflows and prepare data for fine-tuning. By the end of the book, you’ll have the skills to integrate DeepSeek into local deployments, cloud CI/CD pipelines, and custom LLMOps environments.Written by experts with deep knowledge of open-source LLMs and deployment ecosystems, this book is your comprehensive guide to DeepSeek’s capabilities and implementation.
Developing AI Applications. An Introduction
Rheinwerk Publishing, Inc, Metin Karatas
This book opens with a clear introduction to AI fundamentals, covering its history and key concepts while guiding readers through installing essential tools like KNIME and AutoKeras. It begins by building a strong foundation in artificial neural networks and decision trees, enabling readers to grasp core AI methods. The journey then advances to convolutional layers for image classification, transfer learning, and anomaly detection, offering practical, beginner-friendly examples.As the reader progresses, the book explores text classification, cluster analysis, and automated AI model creation with AutoKeras. Visual programming with KNIME is introduced to simplify complex AI workflows. Further chapters cover reinforcement learning and genetic algorithms, expanding the reader’s skill set and preparing them for more advanced challenges. Hands-on exercises throughout reinforce concepts and practical application.In its final chapters, the guide dives into cutting-edge AI tools by demonstrating how to leverage ChatGPT and DALL-E APIs, including prompt engineering and API programming. It concludes with an outlook on the future of AI, equipping readers with the knowledge and confidence to build and deploy their own AI-powered applications from start to finish.
Tim Beattie, Mike Hepburn, Noel O'Connor, Donal...
DevOps Culture and Practice with OpenShift features many different real-world practices - some people-related, some process-related, some technology-related - to facilitate successful DevOps, and in turn OpenShift, adoption within your organization. It introduces many DevOps concepts and tools to connect culture and practice through a continuous loop of discovery, pivots, and delivery underpinned by a foundation of collaboration and software engineering.Containers and container-centric application lifecycle management are now an industry standard, and OpenShift has a leading position in a flourishing market of enterprise Kubernetes-based product offerings. DevOps Culture and Practice with OpenShift provides a roadmap for building empowered product teams within your organization.This guide brings together lean, agile, design thinking, DevOps, culture, facilitation, and hands-on technical enablement all in one book. Through a combination of real-world stories, a practical case study, facilitation guides, and technical implementation details, DevOps Culture and Practice with OpenShift provides tools and techniques to build a DevOps culture within your organization on Red Hat's OpenShift Container Platform.